At present, China’s education reform is developing rapidly, and many schools begin to study and implement school-enterprise cooperative education. There are also some conceptual deviations. In addition, the government’s weak implementation of the guarantee policy for the implementation of combination of school and enterprise education, coupled with the lack of relevant laws and regulations, rarely leads to the success and enthusiasm of combination of school and enterprise education. With the development of collaborative training companies, the participation rate needs to be improved, and the influence of school-enterprise colearning is not significant enough. Therefore, we should do more theoretical research on combination of school and enterprise education, so as to further improve the present situation of combination of school and enterprise education in China and promote the in-depth development of combination of school and enterprise education. At the same time, we should constantly improve relevant practices and systems, improve relevant laws and regulations, learn from the successful experience of cooperation between schools and enterprises training at home and abroad, and design a unique path of cooperation between schools and enterprises in combination with China’s reality. First of all, this paper deeply analyzes the synergy degree of combination of school and enterprise education. By defining the concepts of the combination of industry and teaching and the combination of colleges and enterprises, synergy degree, and cooperative development level, this paper makes an in-depth interpretation of the education and teaching of schools and enterprises. From the perspective of synergetic theory and interactive mechanism, school-enterprise cooperation needs to be strengthened. Secondly, the model is created through the analytic hierarchy process, in which the hierarchical model uses the 10/10-18/2 scaling method to form the classification matrix. Finally, this paper analyzes on the factors affecting the combination of school and enterprise education and puts forward some perfect countermeasures from three angles of government, school, and enterprise.
{"title":"Index Construction and Application of School-Enterprise Collaborative Education Platform Based on AHP Fuzzy Method in Double Creation Education Practice","authors":"Zhenzhen He, Xiuhong Sun","doi":"10.1155/2022/7707384","DOIUrl":"https://doi.org/10.1155/2022/7707384","url":null,"abstract":"At present, China’s education reform is developing rapidly, and many schools begin to study and implement school-enterprise cooperative education. There are also some conceptual deviations. In addition, the government’s weak implementation of the guarantee policy for the implementation of combination of school and enterprise education, coupled with the lack of relevant laws and regulations, rarely leads to the success and enthusiasm of combination of school and enterprise education. With the development of collaborative training companies, the participation rate needs to be improved, and the influence of school-enterprise colearning is not significant enough. Therefore, we should do more theoretical research on combination of school and enterprise education, so as to further improve the present situation of combination of school and enterprise education in China and promote the in-depth development of combination of school and enterprise education. At the same time, we should constantly improve relevant practices and systems, improve relevant laws and regulations, learn from the successful experience of cooperation between schools and enterprises training at home and abroad, and design a unique path of cooperation between schools and enterprises in combination with China’s reality. First of all, this paper deeply analyzes the synergy degree of combination of school and enterprise education. By defining the concepts of the combination of industry and teaching and the combination of colleges and enterprises, synergy degree, and cooperative development level, this paper makes an in-depth interpretation of the education and teaching of schools and enterprises. From the perspective of synergetic theory and interactive mechanism, school-enterprise cooperation needs to be strengthened. Secondly, the model is created through the analytic hierarchy process, in which the hierarchical model uses the 10/10-18/2 scaling method to form the classification matrix. Finally, this paper analyzes on the factors affecting the combination of school and enterprise education and puts forward some perfect countermeasures from three angles of government, school, and enterprise.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"53 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2022-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84865838","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}
5G intelligent sensor network technology realizes the perception, processing, and transmission of information. It forms the three pillars of information technology together with computer technology and communication technology and is an important part of the Internet of Things technology. The 5G smart sensor network is a wireless communication module added to the sensor nodes, and a wireless communication network is formed by a large number of stationary or movable sensor nodes in the form of self-organization and multihop transmission. This paper proposes a keypoint feature extraction method based on deep learning, which can extract keypoint local features for matching. This method uses the convolutional network structure, which is pretrained based on the Siamese network structure and then adjusted to the ternary network structure to continue training to improve the accuracy. This paper proposes a high-art visual communication image classification based on multifeature extraction and classification decision fusion. In the data preprocessing stage, the correlation alignment algorithm is performed on the datasets of different domains (source domain and target domain) to reduce the difference in spatial distribution, and then, a multifeature extractor is designed to extract artistic visual communication images and spatial information. In the process, the multitask learning method is introduced to jointly train the networks of multiple data sets to reduce the degree of overfitting of the model, solve the problem of insufficient labeled samples in the target domain data set, and affect the classification accuracy of high-art visual communication images. Finally, the classification results are obtained through the fusion of voting decisions. The experimental results show that the advantage of this framework is that it utilizes the artistic visual communication image and spatial structure information from the source and target scenes, which can significantly reduce the dependence on the number of labeled samples in the target domain and improve the classification performance. In this paper, a dual-channel deep residual convolutional neural network is designed. The multiple convolution layers of the residual module in the network use hard parameters to share, so that the deep feature representation on the joint spatial spectrum dimension can be automatically extracted. The features extracted by the network are transferred to maximize the auxiliary role of the labeled samples in the source domain and avoid the negative transfer problem caused by the forced transfer between irrelevant samples.
{"title":"Feature Extraction Method of Art Visual Communication Image Based on 5G Intelligent Sensor Network","authors":"Wei-Dan Liang","doi":"10.1155/2022/8545345","DOIUrl":"https://doi.org/10.1155/2022/8545345","url":null,"abstract":"5G intelligent sensor network technology realizes the perception, processing, and transmission of information. It forms the three pillars of information technology together with computer technology and communication technology and is an important part of the Internet of Things technology. The 5G smart sensor network is a wireless communication module added to the sensor nodes, and a wireless communication network is formed by a large number of stationary or movable sensor nodes in the form of self-organization and multihop transmission. This paper proposes a keypoint feature extraction method based on deep learning, which can extract keypoint local features for matching. This method uses the convolutional network structure, which is pretrained based on the Siamese network structure and then adjusted to the ternary network structure to continue training to improve the accuracy. This paper proposes a high-art visual communication image classification based on multifeature extraction and classification decision fusion. In the data preprocessing stage, the correlation alignment algorithm is performed on the datasets of different domains (source domain and target domain) to reduce the difference in spatial distribution, and then, a multifeature extractor is designed to extract artistic visual communication images and spatial information. In the process, the multitask learning method is introduced to jointly train the networks of multiple data sets to reduce the degree of overfitting of the model, solve the problem of insufficient labeled samples in the target domain data set, and affect the classification accuracy of high-art visual communication images. Finally, the classification results are obtained through the fusion of voting decisions. The experimental results show that the advantage of this framework is that it utilizes the artistic visual communication image and spatial structure information from the source and target scenes, which can significantly reduce the dependence on the number of labeled samples in the target domain and improve the classification performance. In this paper, a dual-channel deep residual convolutional neural network is designed. The multiple convolution layers of the residual module in the network use hard parameters to share, so that the deep feature representation on the joint spatial spectrum dimension can be automatically extracted. The features extracted by the network are transferred to maximize the auxiliary role of the labeled samples in the source domain and avoid the negative transfer problem caused by the forced transfer between irrelevant samples.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"10 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81907160","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 traditional way of museum exhibition is physical exhibition, which is essentially restricted by the venue, time, space, and display conditions and is no longer applicable to the display form of modern museum exhibits. Therefore, with the development of a large number of modern technologies such as information technology, wireless sensor technology and image processing technology, the way of museum cultural relics display also tends to be more intelligent and intelligent. Based on this, this paper will set up corresponding gateway nodes, routing nodes, and corresponding terminal nodes for each node of the corresponding museum based on the intelligent wireless sensor network technology; transmit the audio impact information of the corresponding museum exhibits through the terminal nodes; and automatically send the node short address information of the corresponding information to the corresponding analysis end in real time for analysis and processing, and then based on the information characteristics of the corresponding exhibits, at the same time, combined with virtual fusion and human-computer interaction technology, a set of augmented reality application system for tourist mobile terminal is developed. Abandoning the disadvantages of traditional museum display methods, this paper creatively designs the corresponding museum heritage intelligent display workflow based on intelligent wireless sensor network through C/S architecture and finally realizes the enhancement effect of virtual reality on tourism terminals. In order to verify the superiority of the intelligent display mode of museum cultural relics based on intelligent wireless sensor network proposed in this paper, this paper compares it with the traditional display mode. The experimental results show that this paper has obvious advantages in the display comprehensiveness, visitor satisfaction, and display effectiveness, which further improves the effect of museum cultural relics display.
{"title":"Optimization of Intelligent Display Mode of Museum Cultural Relics Based on Intelligent Wireless Sensor Network","authors":"Luolan Shen","doi":"10.1155/2022/1961700","DOIUrl":"https://doi.org/10.1155/2022/1961700","url":null,"abstract":"The traditional way of museum exhibition is physical exhibition, which is essentially restricted by the venue, time, space, and display conditions and is no longer applicable to the display form of modern museum exhibits. Therefore, with the development of a large number of modern technologies such as information technology, wireless sensor technology and image processing technology, the way of museum cultural relics display also tends to be more intelligent and intelligent. Based on this, this paper will set up corresponding gateway nodes, routing nodes, and corresponding terminal nodes for each node of the corresponding museum based on the intelligent wireless sensor network technology; transmit the audio impact information of the corresponding museum exhibits through the terminal nodes; and automatically send the node short address information of the corresponding information to the corresponding analysis end in real time for analysis and processing, and then based on the information characteristics of the corresponding exhibits, at the same time, combined with virtual fusion and human-computer interaction technology, a set of augmented reality application system for tourist mobile terminal is developed. Abandoning the disadvantages of traditional museum display methods, this paper creatively designs the corresponding museum heritage intelligent display workflow based on intelligent wireless sensor network through C/S architecture and finally realizes the enhancement effect of virtual reality on tourism terminals. In order to verify the superiority of the intelligent display mode of museum cultural relics based on intelligent wireless sensor network proposed in this paper, this paper compares it with the traditional display mode. The experimental results show that this paper has obvious advantages in the display comprehensiveness, visitor satisfaction, and display effectiveness, which further improves the effect of museum cultural relics display.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"53 59 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76486950","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 China’s modern market economy under the rapid development of the general situation, we work more and more problems, and work pressure is also increasing. The so-called office space refers to the space layout, style, and the physical and psychological division of the space. Office space must take into account many factors, involving technology, technology, humanities, aesthetics, and other elements, while the office space is the space where people work and relax. In recent years, as people’s requirements for the work environment are increasingly high, therefore, the design of the office space is also more and more attention to people. The concept of soft furnishing design into the work space will help improve the overall corporate and office space design of cultural taste which is one of the main methods to show the quality and human connotation of the enterprise. The three-dimensional reconstruction refers to the creation of a mathematical model suitable for computer display and processing of three-dimensional space objects. It is an important basic tool for data processing, computing, and researching the performance of mathematical models in the computer environment, which can be applied in various fields such as autonomous navigation of mobile robots, aviation and remote sensing computing, industrial monitoring information system, medical imaging, and virtual reality. The 3D environment reconstruction technology has become one of the popular research areas in computer vision and increasingly attracts the attention of design practitioners. This paper takes the 3D environment reconstruction technology of office space soft decoration design as the basis and discusses the important elements and modeling ideas in soft decoration design, which adds to the interior design of office space, and uses Kinect to obtain the depth data in the 3D environment, so as to complete the realistic 3D reproduction of the interior environment based on computer vision technology.
{"title":"Spatial Expression of Multifaceted Soft Decoration Elements: Application of 3D Reconstruction Algorithm in Soft Decoration and Furnishing Design of Office Space","authors":"Ping Yao","doi":"10.1155/2022/5345293","DOIUrl":"https://doi.org/10.1155/2022/5345293","url":null,"abstract":"In China’s modern market economy under the rapid development of the general situation, we work more and more problems, and work pressure is also increasing. The so-called office space refers to the space layout, style, and the physical and psychological division of the space. Office space must take into account many factors, involving technology, technology, humanities, aesthetics, and other elements, while the office space is the space where people work and relax. In recent years, as people’s requirements for the work environment are increasingly high, therefore, the design of the office space is also more and more attention to people. The concept of soft furnishing design into the work space will help improve the overall corporate and office space design of cultural taste which is one of the main methods to show the quality and human connotation of the enterprise. The three-dimensional reconstruction refers to the creation of a mathematical model suitable for computer display and processing of three-dimensional space objects. It is an important basic tool for data processing, computing, and researching the performance of mathematical models in the computer environment, which can be applied in various fields such as autonomous navigation of mobile robots, aviation and remote sensing computing, industrial monitoring information system, medical imaging, and virtual reality. The 3D environment reconstruction technology has become one of the popular research areas in computer vision and increasingly attracts the attention of design practitioners. This paper takes the 3D environment reconstruction technology of office space soft decoration design as the basis and discusses the important elements and modeling ideas in soft decoration design, which adds to the interior design of office space, and uses Kinect to obtain the depth data in the 3D environment, so as to complete the realistic 3D reproduction of the interior environment based on computer vision technology.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"6 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75618345","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}
After the outbreak of the epidemic, the external environment has changed, affecting social and economic development. In the unfavorable economic and social environment, the behavior of many businesses and consumers has also changed. Therefore, companies do not have enough income and expenditure, which leads to the breakage of their capital chain or even bankruptcy. As a result, proper financing has been critical for many businesses in the near term. Today, listed companies are mainly financed from internal financing, equity, and debt. Generally speaking, most companies prefer debt financing because equity financing costs can be deducted before taxes and investment costs are lower than equity financing. Enterprises face certain risks when choosing debt financing; in addition, they also face the risk of future repayment. This paper adopts the research method of DEA-Malmquist index for analysis, which can effectively help enterprises avoid or reduce the risk of debt financing and is worthy of in-depth research and exploration by entrepreneurs and scholars.
{"title":"Risk Mechanism and Architecture of Investment and Financing Based on DEA-Malmquist Index","authors":"Jun-Wei Chu","doi":"10.1155/2022/3613624","DOIUrl":"https://doi.org/10.1155/2022/3613624","url":null,"abstract":"After the outbreak of the epidemic, the external environment has changed, affecting social and economic development. In the unfavorable economic and social environment, the behavior of many businesses and consumers has also changed. Therefore, companies do not have enough income and expenditure, which leads to the breakage of their capital chain or even bankruptcy. As a result, proper financing has been critical for many businesses in the near term. Today, listed companies are mainly financed from internal financing, equity, and debt. Generally speaking, most companies prefer debt financing because equity financing costs can be deducted before taxes and investment costs are lower than equity financing. Enterprises face certain risks when choosing debt financing; in addition, they also face the risk of future repayment. This paper adopts the research method of DEA-Malmquist index for analysis, which can effectively help enterprises avoid or reduce the risk of debt financing and is worthy of in-depth research and exploration by entrepreneurs and scholars.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"457 1","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77029298","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 view of the scene’s complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability.
{"title":"Scene Classification Using Deep Networks Combined with Visual Attention","authors":"Jing Shi, Hong Zhu, Yuxing Li, Yanghui Li, Sen Du","doi":"10.1155/2022/7191537","DOIUrl":"https://doi.org/10.1155/2022/7191537","url":null,"abstract":"In view of the scene’s complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"40 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73988723","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}
Teacher professional education development is actually another type of development that crosses over into a category of teacher training development that encompasses two other types of teacher training—one of which is formal and the other is informal teacher training. The other approach to teacher professional development is quite different from the professional development of professional education. The focus of the professional development of teachers is a dynamic process of development in which teachers take the initiative, actively, and consciously pursue the direction of professional development of teachers. Therefore, how to observe and study the direction of teachers’ professional development from the perspective of teachers is an urgent problem that needs to be studied and solved. The professional development of teachers should be combined with their own social and teaching lives. In addition, information technology should be integrated into teachers’ daily teaching life, so that it can be used as a tool to support teachers’ professional development. Information technology has gradually become a tool and a means that teachers cannot do without in their teaching lives, so it is important to study and think about it from various aspects, such as the teaching process and teachers’ growth experiences, and to continuously study teachers’ professional development. Therefore, it is necessary to study how information technology can be used well by teachers and used by teachers to become a useful tool in teachers’ educational and teaching work from various aspects. This paper first argues that the main goal of teachers’ professional development is to gradually grow into expert teachers, while the main content of teachers’ professional development is to understand practical knowledge, and the specific tool used by teachers in teaching is the application of social software support that can support teachers’ professional development (Romanowski and Alkhateeb, 2022). This paper envisages that information technology can be integrated into the entire teaching environment and the teaching process of teachers, as a tool and a means to make the content of teachers’ teaching more concise and clear. Through the use of information technology and other tools, teachers can gradually identify what they need to improve and add to their teaching process, lay the foundation for their future development, and pave the way to become better teachers with a clearer plan for their future development.
教师专业教育发展实际上是另一种类型的发展，它跨越了教师培训发展的范畴，包括另外两种类型的教师培训——一种是正式的，另一种是非正式的教师培训。教师专业发展的另一种途径与专业教育的专业发展截然不同。教师专业发展的焦点是教师主动、主动、自觉地追求教师专业发展方向的动态发展过程。因此，如何站在教师的角度来观察和研究教师专业发展的方向，是一个迫切需要研究和解决的问题。教师的专业发展应与自己的社会生活和教学生活相结合。此外，应将信息技术融入教师的日常教学生活中，使其成为支持教师专业发展的工具。信息技术已经逐渐成为教师在教学生活中不可缺少的工具和手段，因此从教学过程、教师成长经历等各个方面对其进行研究和思考，不断研究教师的专业发展是非常重要的。因此，有必要从各个方面研究信息技术如何为教师所用，为教师所用，使信息技术成为教师教育教学工作中的有用工具。本文首先认为教师专业发展的主要目标是逐步成长为专家型教师，而教师专业发展的主要内容是理解实用知识，教师在教学中使用的具体工具是能够支持教师专业发展的社交软件支持的应用(Romanowski and Alkhateeb, 2022)。本文设想将信息技术融入到教师的整个教学环境和教学过程中，作为一种工具和手段，使教师的教学内容更加简洁明了。通过使用信息技术等工具，教师可以逐渐发现自己在教学过程中需要改进和增加的地方，为自己的未来发展奠定基础，为自己成为更好的教师铺平道路，对自己的未来发展有更清晰的规划。
{"title":"A Forward-Looking Study on the In-Depth Development Planning of Information Technology into Teacher Education","authors":"Chunlan Zhang","doi":"10.1155/2022/4885771","DOIUrl":"https://doi.org/10.1155/2022/4885771","url":null,"abstract":"Teacher professional education development is actually another type of development that crosses over into a category of teacher training development that encompasses two other types of teacher training—one of which is formal and the other is informal teacher training. The other approach to teacher professional development is quite different from the professional development of professional education. The focus of the professional development of teachers is a dynamic process of development in which teachers take the initiative, actively, and consciously pursue the direction of professional development of teachers. Therefore, how to observe and study the direction of teachers’ professional development from the perspective of teachers is an urgent problem that needs to be studied and solved. The professional development of teachers should be combined with their own social and teaching lives. In addition, information technology should be integrated into teachers’ daily teaching life, so that it can be used as a tool to support teachers’ professional development. Information technology has gradually become a tool and a means that teachers cannot do without in their teaching lives, so it is important to study and think about it from various aspects, such as the teaching process and teachers’ growth experiences, and to continuously study teachers’ professional development. Therefore, it is necessary to study how information technology can be used well by teachers and used by teachers to become a useful tool in teachers’ educational and teaching work from various aspects. This paper first argues that the main goal of teachers’ professional development is to gradually grow into expert teachers, while the main content of teachers’ professional development is to understand practical knowledge, and the specific tool used by teachers in teaching is the application of social software support that can support teachers’ professional development (Romanowski and Alkhateeb, 2022). This paper envisages that information technology can be integrated into the entire teaching environment and the teaching process of teachers, as a tool and a means to make the content of teachers’ teaching more concise and clear. Through the use of information technology and other tools, teachers can gradually identify what they need to improve and add to their teaching process, lay the foundation for their future development, and pave the way to become better teachers with a clearer plan for their future development.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"99 1","pages":"1-11"},"PeriodicalIF":0.0,"publicationDate":"2022-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82724063","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}
Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).
{"title":"Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS","authors":"Harsh Khatter, Pooja Malik, Amrita Jyoti, A. Ahlawat, Gaurav Dubey, Anurag Mishra, Sanjeev Chandra Neupane","doi":"10.1155/2022/7242557","DOIUrl":"https://doi.org/10.1155/2022/7242557","url":null,"abstract":"Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"53 22 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80473793","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 accurately and effectively mine relevant users in social networks, we can stop false information and illegal activities in the network, thereby ensuring the safety and integrity of the network environment. A method is proposed for the implementation of a data mining algorithm of a user network based on the fusion of several data. AUMA-MRL (associated user mining algorithm based on multi-information representation learning) proposes an associated user mining algorithm based on node characteristics, neighborhood information, and global network structure information. The steps of the algorithm are as follows: combining each user of the social network into a node using a method where each node is installed separately and combining network user characteristics and user relationship information. A user pair is a network similarity vector that represents the similarity of users in different dimensions. Based on these similarity vectors, a corresponding user separation algorithm is formed. It examines the feasibility and efficiency of the AUMA-MRL algorithm for researching relevant users. The proportion of associated users in the network to be fused is lower than that of nonassociated users, and the prediction has little effect on improving the recall rate of nonassociated users, so the recall rate is slightly lower than the accuracy. This algorithm can quickly get the embedding of new nodes and the similarity vector between new nodes and other nodes in the network, so as to quickly mine the associated users of new nodes in the network and enhance the robustness of the network associated user mining algorithm.
{"title":"Implementation of Network Data Mining Algorithm for Associated Users Based on Multi-Information Fusion","authors":"Hui Zhang","doi":"10.1155/2022/3350997","DOIUrl":"https://doi.org/10.1155/2022/3350997","url":null,"abstract":"In order to accurately and effectively mine relevant users in social networks, we can stop false information and illegal activities in the network, thereby ensuring the safety and integrity of the network environment. A method is proposed for the implementation of a data mining algorithm of a user network based on the fusion of several data. AUMA-MRL (associated user mining algorithm based on multi-information representation learning) proposes an associated user mining algorithm based on node characteristics, neighborhood information, and global network structure information. The steps of the algorithm are as follows: combining each user of the social network into a node using a method where each node is installed separately and combining network user characteristics and user relationship information. A user pair is a network similarity vector that represents the similarity of users in different dimensions. Based on these similarity vectors, a corresponding user separation algorithm is formed. It examines the feasibility and efficiency of the AUMA-MRL algorithm for researching relevant users. The proportion of associated users in the network to be fused is lower than that of nonassociated users, and the prediction has little effect on improving the recall rate of nonassociated users, so the recall rate is slightly lower than the accuracy. This algorithm can quickly get the embedding of new nodes and the similarity vector between new nodes and other nodes in the network, so as to quickly mine the associated users of new nodes in the network and enhance the robustness of the network associated user mining algorithm.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"42 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80939564","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}
Sebastin Suresh, Vishnunarayan Girishan Prabhu, V. Parthasarathy, R. Boddu, Y. Sucharitha, Gemmachis Teshite
The battery power limits the energy consumption of wireless sensor networks (WSN). As a result, its network performance suffered significantly. Therefore, this paper proposes an opportunistic energy-efficient routing protocol (OEERP) algorithm for reducing network energy consumption. It provides accurate target location detection, energy efficiency, and network lifespan extension. It is intended to schedule idle nodes into a sleep state, thereby optimising network energy consumption. Sleep is dynamically adjusted based on the network’s residual energy (RE) and flow rate (FR). It saves energy for a longer period. The sleep nodes are triggered to wake up after a certain time interval. The simulation results show that the proposed OEERP algorithm outperforms existing state-of-the-art algorithms in terms of accuracy, energy efficiency, and network lifetime extension.
{"title":"A Novel Routing Protocol for Low-Energy Wireless Sensor Networks","authors":"Sebastin Suresh, Vishnunarayan Girishan Prabhu, V. Parthasarathy, R. Boddu, Y. Sucharitha, Gemmachis Teshite","doi":"10.1155/2022/8244176","DOIUrl":"https://doi.org/10.1155/2022/8244176","url":null,"abstract":"The battery power limits the energy consumption of wireless sensor networks (WSN). As a result, its network performance suffered significantly. Therefore, this paper proposes an opportunistic energy-efficient routing protocol (OEERP) algorithm for reducing network energy consumption. It provides accurate target location detection, energy efficiency, and network lifespan extension. It is intended to schedule idle nodes into a sleep state, thereby optimising network energy consumption. Sleep is dynamically adjusted based on the network’s residual energy (RE) and flow rate (FR). It saves energy for a longer period. The sleep nodes are triggered to wake up after a certain time interval. The simulation results show that the proposed OEERP algorithm outperforms existing state-of-the-art algorithms in terms of accuracy, energy efficiency, and network lifetime extension.","PeriodicalId":14776,"journal":{"name":"J. Sensors","volume":"80 5 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2022-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90946756","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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