Pub Date : 2022-02-10DOI: 10.1142/s0219265921440072
B. Lin, I. Tlili, M. Baseer
A Smart Hybrid Home (SHH) system studies power concerns for individual clients with an off-grid electricity connection are studied in a Smart Hybrid Home (SHH) system. The creation of autonomous hybrid electricity systems has been regarded as a way to improve energy independence. The primary objective is to ensure efficient management of energy. Detailed modeling is proposed in which the solar energy component is regarded as the significant source to achieve this aim. A multi-agent energy management system (MA-EMS) is presented in this article. It also includes the storing devices for power (Fuel Cell/Capacitors) for safe power delivery. The technical performance of the decentralised solution is in line with the existing central solution, which offers improved financially and operationally for the implementation and operation of the autonomous method. Furthermore, an IT-management system is created and described to guarantee that the system functions correctly utilizing a multi-agent structure. The proposed electricity management system is meant to recognize multi-agent jobs and comprehend probable situations based on energy attributes and requirements. The findings showed that the method suggested meets the aims of an operational database taken from different climatic services using the Matlab/Simulink Application set for the Smart Electricity Management Method. By implementing the proposed technique the power consumption is increased to 410[Formula: see text]kw, and it improves the efficiency rate to 88.4%.
{"title":"Multi-agent System with an Optimized Heuristic Algorithm for Energy Management Solutions","authors":"B. Lin, I. Tlili, M. Baseer","doi":"10.1142/s0219265921440072","DOIUrl":"https://doi.org/10.1142/s0219265921440072","url":null,"abstract":"A Smart Hybrid Home (SHH) system studies power concerns for individual clients with an off-grid electricity connection are studied in a Smart Hybrid Home (SHH) system. The creation of autonomous hybrid electricity systems has been regarded as a way to improve energy independence. The primary objective is to ensure efficient management of energy. Detailed modeling is proposed in which the solar energy component is regarded as the significant source to achieve this aim. A multi-agent energy management system (MA-EMS) is presented in this article. It also includes the storing devices for power (Fuel Cell/Capacitors) for safe power delivery. The technical performance of the decentralised solution is in line with the existing central solution, which offers improved financially and operationally for the implementation and operation of the autonomous method. Furthermore, an IT-management system is created and described to guarantee that the system functions correctly utilizing a multi-agent structure. The proposed electricity management system is meant to recognize multi-agent jobs and comprehend probable situations based on energy attributes and requirements. The findings showed that the method suggested meets the aims of an operational database taken from different climatic services using the Matlab/Simulink Application set for the Smart Electricity Management Method. By implementing the proposed technique the power consumption is increased to 410[Formula: see text]kw, and it improves the efficiency rate to 88.4%.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127816951","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}
Pub Date : 2022-02-10DOI: 10.1142/s021926592143043x
Daiwen Wu
The application and management system of scientific research projects adopts the mature B/S mode, and uses the technologies of jqGrid, Layui, jQuery, PHP and MYSQL to design and realize the function modules of project application, online evaluation, project process management and project query statistics. At present, as a comprehensive management system of Weinan science and technology business, the system has been officially put into use, and has completed the application and evaluation of Weinan science and technology plan projects since 2018. The system is stable, beautiful interface, easy to operate, and can meet the daily needs of science and technology project management. It has produced certain economic and social benefits, and the system has certain application and promotion value in colleges and universities, scientific research institutes, science and technology management departments and other similar units.
{"title":"The Application and Management System of Scientific Research Projects Based on PHP and MySQL","authors":"Daiwen Wu","doi":"10.1142/s021926592143043x","DOIUrl":"https://doi.org/10.1142/s021926592143043x","url":null,"abstract":"The application and management system of scientific research projects adopts the mature B/S mode, and uses the technologies of jqGrid, Layui, jQuery, PHP and MYSQL to design and realize the function modules of project application, online evaluation, project process management and project query statistics. At present, as a comprehensive management system of Weinan science and technology business, the system has been officially put into use, and has completed the application and evaluation of Weinan science and technology plan projects since 2018. The system is stable, beautiful interface, easy to operate, and can meet the daily needs of science and technology project management. It has produced certain economic and social benefits, and the system has certain application and promotion value in colleges and universities, scientific research institutes, science and technology management departments and other similar units.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"54 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128455860","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921420202
Qinglin Wang, Yingzhi Tian, Lihua Feng
Let [Formula: see text] be a hypergraph, where [Formula: see text] is a set of vertices and [Formula: see text] is a set of non-empty subsets of [Formula: see text] called edges. If all edges of [Formula: see text] have the same cardinality [Formula: see text], then [Formula: see text] is an [Formula: see text]-uniform hypergraph. A hypergraph [Formula: see text] is called a hypersubgraph of a hypergraph [Formula: see text] if [Formula: see text] and [Formula: see text]. The [Formula: see text]-[Formula: see text] of hypergraph [Formula: see text], denoted by [Formula: see text], is the cardinality of a minimum vertex set [Formula: see text] such that [Formula: see text] is disconnected or is a trival hypergraph. We call [Formula: see text] [Formula: see text]-[Formula: see text] if [Formula: see text]. Tian, Lai and Meng [Y. Z. Tian, H.-J. Lai, J. X. Meng, On the sizes of vertex-[Formula: see text]-maximal [Formula: see text]-uniform hypergraphs, Graphs and Combinatorics 35(5) (2019) 1001–1010] conjectered that, for sufficiently large [Formula: see text], every [Formula: see text]-vertex [Formula: see text]-uniform hypergraph with no [Formula: see text]-connected hypersubgraphs has at most [Formula: see text] edges. This upper bound is equal to [Formula: see text] when [Formula: see text]. In this paper, we prove that for [Formula: see text] and [Formula: see text], every [Formula: see text]-vertex [Formula: see text]-uniform hypergraph with no [Formula: see text]-connected hypersubgraphs has at most [Formula: see text] edges.
设[Formula: see text]为超图，其中[Formula: see text]是顶点的集合，[Formula: see text]是[Formula: see text]的非空子集的集合，称为边。如果[Formula: see text]的所有边具有相同的基数[Formula: see text]，则[Formula: see text]是一个[Formula: see text]-均匀超图。如果[公式:见文]和[公式:见文]，则超图[公式:见文]称为超图[公式:见文]的超子图。[公式:见文]-超图[公式:见文]的[公式:见文]，用[公式:见文]表示，是一个最小顶点集[公式:见文]的基数，使得[公式:见文]是不相连的或者是一个平凡的超图。我们称[公式:见文][公式:见文]-[公式:见文]如果[公式:见文]。田，赖，孟[Y]。田志杰，h - j。Lai, J. X. Meng，关于顶点的大小-[公式:见文]-极大[公式:见文]-均匀超图，图与组合35(5)(2019)1001-1010]推测，对于足够大的[公式:见文]，每个[公式:见文]-顶点[公式:见文]-均匀超图没有[公式:见文]-连通超图最多有[公式:见文]条边。当[公式:见文]时，这个上界等于[公式:见文]。本文证明了对于[公式:见文]和[公式:见文]，每个[公式:见文]-顶点[公式:见文]-没有[公式:见文]-连通超子图的一致超图最多有[公式:见文]条边。
{"title":"On the Number of Edges in a 3-Uniform Hypergraph with No (k + 1)-Connected Hypersubgraphs","authors":"Qinglin Wang, Yingzhi Tian, Lihua Feng","doi":"10.1142/s0219265921420202","DOIUrl":"https://doi.org/10.1142/s0219265921420202","url":null,"abstract":"Let [Formula: see text] be a hypergraph, where [Formula: see text] is a set of vertices and [Formula: see text] is a set of non-empty subsets of [Formula: see text] called edges. If all edges of [Formula: see text] have the same cardinality [Formula: see text], then [Formula: see text] is an [Formula: see text]-uniform hypergraph. A hypergraph [Formula: see text] is called a hypersubgraph of a hypergraph [Formula: see text] if [Formula: see text] and [Formula: see text]. The [Formula: see text]-[Formula: see text] of hypergraph [Formula: see text], denoted by [Formula: see text], is the cardinality of a minimum vertex set [Formula: see text] such that [Formula: see text] is disconnected or is a trival hypergraph. We call [Formula: see text] [Formula: see text]-[Formula: see text] if [Formula: see text]. Tian, Lai and Meng [Y. Z. Tian, H.-J. Lai, J. X. Meng, On the sizes of vertex-[Formula: see text]-maximal [Formula: see text]-uniform hypergraphs, Graphs and Combinatorics 35(5) (2019) 1001–1010] conjectered that, for sufficiently large [Formula: see text], every [Formula: see text]-vertex [Formula: see text]-uniform hypergraph with no [Formula: see text]-connected hypersubgraphs has at most [Formula: see text] edges. This upper bound is equal to [Formula: see text] when [Formula: see text]. In this paper, we prove that for [Formula: see text] and [Formula: see text], every [Formula: see text]-vertex [Formula: see text]-uniform hypergraph with no [Formula: see text]-connected hypersubgraphs has at most [Formula: see text] edges.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122380483","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921470150
Yihao Tian
University students face immense challenges in current situations in ideological and political research. Therefore, the way ideological work constantly needs to be adapted, and the exchange of advanced experience strengthened to increase ideological and political education (IPE) in universities. Specific methods of university administration may include only ideological and political courses. Courses information and student grades did not conduct an ideological or political evaluation of the student. They assessed the psychological behaviors of the student based on their success, nor did them include clear information on the course schedule for specific ideological and political courses. This article, Supervised learning-based teaching evaluation approach (SL-TEA), has been proposed to focus on supervised learning from ideas about machine learning technology and the current IPE status, to be developed using a brief analysis procedure. Supervised learning uses a practice set to provide the necessary quality through teaching models. Inputs and correct outputs that allow the model to learn over time are part of this training data. The study uses the system of experts to manage, operate and monitor model evaluation data and create a related database for a real-time update. Besides, to check the impact of the model and to run simulation tests. This study SL-TEA model follows the real needs of the system that the ideological and political teaching content of colleges and colleges can be evaluated. Thus, the experimental results show the better performance through the highest student accuracy ratio of 97.1 %, a high-performance ratio of 94.3%, improved political thinking rate of 92.8%, improved actual positive rate of 90.2%, the false-positive rate of 92.2%, enhance learning rate of 96.6% and reduce the error rate 21.2%, compared to other methods.
{"title":"Teaching Effect Evaluation System of Ideological and Political Teaching Based on Supervised Learning","authors":"Yihao Tian","doi":"10.1142/s0219265921470150","DOIUrl":"https://doi.org/10.1142/s0219265921470150","url":null,"abstract":"University students face immense challenges in current situations in ideological and political research. Therefore, the way ideological work constantly needs to be adapted, and the exchange of advanced experience strengthened to increase ideological and political education (IPE) in universities. Specific methods of university administration may include only ideological and political courses. Courses information and student grades did not conduct an ideological or political evaluation of the student. They assessed the psychological behaviors of the student based on their success, nor did them include clear information on the course schedule for specific ideological and political courses. This article, Supervised learning-based teaching evaluation approach (SL-TEA), has been proposed to focus on supervised learning from ideas about machine learning technology and the current IPE status, to be developed using a brief analysis procedure. Supervised learning uses a practice set to provide the necessary quality through teaching models. Inputs and correct outputs that allow the model to learn over time are part of this training data. The study uses the system of experts to manage, operate and monitor model evaluation data and create a related database for a real-time update. Besides, to check the impact of the model and to run simulation tests. This study SL-TEA model follows the real needs of the system that the ideological and political teaching content of colleges and colleges can be evaluated. Thus, the experimental results show the better performance through the highest student accuracy ratio of 97.1 %, a high-performance ratio of 94.3%, improved political thinking rate of 92.8%, improved actual positive rate of 90.2%, the false-positive rate of 92.2%, enhance learning rate of 96.6% and reduce the error rate 21.2%, compared to other methods.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129260423","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921470149
Yinan Zhang
Depending on the rapid growth of technology and computer science and globalization, increasing universities and various training programs are expected to achieve increasing lifelong education currently. Based on the increase of visual saturation, one of these programs is undoubtedly visual arts creation. Nowadays, there is a need to reconsider the content of art education and arts programs in the light of modern art productions, changing aesthetic judgments, and social changes.One of the most challenging tasks an art teacher faces in today‘s classroom is explaining the meaning behind the art that is sometimes deemed meaningless or shocking. Hence, in this paper, Deep Learning Algorithm (DLA) has been proposed for modern art education.Profound learning outcomes in the art world shifted people’s traditional views; more and more people consider that when AI eventually eliminates artists, it is not a long way. To examine the algorithm’s performance in practise, experimental assessment exposes it to learning tasks. Such algorithmic features are frequently evaluated independently in terms of performance while learning a model, i.e. at training time, and performance while applying a learnt model, i.e. at test time. This article discusses the implementation of deep learning in drawing, music, literature, and describes the classical models and algorithms in those fields of art. One of the most significant aspects of utilising a deep learning technique is its capacity to perform feature engineering on its own. In this technique, an algorithm searches the data for characteristics that correlate and then combines together to facilitate quicker learning without being expressly directed to provide it. The proposed method supports a comprehensive approach to teaching and learning in the arts and outlines standards and skills for the art teacher in the content of art, knowledge of the students, instruction, curriculum development, and evaluation of student learning outcomes, program, and teacher effectiveness.
{"title":"Modern Art Design System Based on the Deep Learning Algorithm","authors":"Yinan Zhang","doi":"10.1142/s0219265921470149","DOIUrl":"https://doi.org/10.1142/s0219265921470149","url":null,"abstract":"Depending on the rapid growth of technology and computer science and globalization, increasing universities and various training programs are expected to achieve increasing lifelong education currently. Based on the increase of visual saturation, one of these programs is undoubtedly visual arts creation. Nowadays, there is a need to reconsider the content of art education and arts programs in the light of modern art productions, changing aesthetic judgments, and social changes.One of the most challenging tasks an art teacher faces in today‘s classroom is explaining the meaning behind the art that is sometimes deemed meaningless or shocking. Hence, in this paper, Deep Learning Algorithm (DLA) has been proposed for modern art education.Profound learning outcomes in the art world shifted people’s traditional views; more and more people consider that when AI eventually eliminates artists, it is not a long way. To examine the algorithm’s performance in practise, experimental assessment exposes it to learning tasks. Such algorithmic features are frequently evaluated independently in terms of performance while learning a model, i.e. at training time, and performance while applying a learnt model, i.e. at test time. This article discusses the implementation of deep learning in drawing, music, literature, and describes the classical models and algorithms in those fields of art. One of the most significant aspects of utilising a deep learning technique is its capacity to perform feature engineering on its own. In this technique, an algorithm searches the data for characteristics that correlate and then combines together to facilitate quicker learning without being expressly directed to provide it. The proposed method supports a comprehensive approach to teaching and learning in the arts and outlines standards and skills for the art teacher in the content of art, knowledge of the students, instruction, curriculum development, and evaluation of student learning outcomes, program, and teacher effectiveness.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125633469","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921430271
Xianwen Qi, Xiaomeng Li
To strengthen urban tourism sustainable development, this paper puts forward the extraction method of tourism sustainable development path under the background of artificial intelligence [Formula: see text] smart city construction. Based on the conceptual model of influencing factors of smart city sustainable development, this paper analyzes the connotation of latent variables. And we are designing a structural analysis model to analyze the current situation of urban tourism sustainable development, analyzing the total effect of parameter factors, formulating the path of smart city tourism sustainable development corresponding to the parameters, and taking Anhui Province as an example. To guide the construction and perfection of the industrial chain of the smart city’s sustainable development of industrial tourism, this paper constructs the system model of smart city, analyses the sustainable development model of Anhui smart city, and designs the extraction method of the sustainable development path of intelligent city tourism.
{"title":"Extraction Method of Tourism Sustainable Development Path under the Background of Artificial Intelligence + Smart City Construction","authors":"Xianwen Qi, Xiaomeng Li","doi":"10.1142/s0219265921430271","DOIUrl":"https://doi.org/10.1142/s0219265921430271","url":null,"abstract":"To strengthen urban tourism sustainable development, this paper puts forward the extraction method of tourism sustainable development path under the background of artificial intelligence [Formula: see text] smart city construction. Based on the conceptual model of influencing factors of smart city sustainable development, this paper analyzes the connotation of latent variables. And we are designing a structural analysis model to analyze the current situation of urban tourism sustainable development, analyzing the total effect of parameter factors, formulating the path of smart city tourism sustainable development corresponding to the parameters, and taking Anhui Province as an example. To guide the construction and perfection of the industrial chain of the smart city’s sustainable development of industrial tourism, this paper constructs the system model of smart city, analyses the sustainable development model of Anhui smart city, and designs the extraction method of the sustainable development path of intelligent city tourism.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125753225","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921470216
Xu Yang
In the special performance prediction model of dance cadets, the physical form quality index is regarded as the dependent variable and the special achievement is regarded as the dependent variable. The results of association analysis and cluster analysis showthat there are 6 specific items of higher sensitivity in body shape, physical quality and special quality. Neural network is adopted to build prediction model, and reliability and error analysis are carried out for this model. The test results show that the model constructed by the neural network is more accurate than the regression model to predict the dance performance and the development level of the physical quality.
{"title":"Analysis of the Construction of Dance Teaching System Based on Digital Media Technology","authors":"Xu Yang","doi":"10.1142/s0219265921470216","DOIUrl":"https://doi.org/10.1142/s0219265921470216","url":null,"abstract":"In the special performance prediction model of dance cadets, the physical form quality index is regarded as the dependent variable and the special achievement is regarded as the dependent variable. The results of association analysis and cluster analysis showthat there are 6 specific items of higher sensitivity in body shape, physical quality and special quality. Neural network is adopted to build prediction model, and reliability and error analysis are carried out for this model. The test results show that the model constructed by the neural network is more accurate than the regression model to predict the dance performance and the development level of the physical quality.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129260350","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921430258
Li Zhang, Sudhakar Sengan, P. Manivannan
Socially, politically, and morally, the world of sport is still changing. On the other hand, technology has been the most prevalent transition in the sport over the last century. Thanks to modern science, athletes can now go higher, run quicker, and, most importantly, remain healthy. Although academics, agencies, and policymakers had already urged physical education teachers to use technology in their classrooms, in many of these situations, technology is used for administrative purposes, including tracking enrolment and measuring, documenting, and reporting students’ work. Thus, this paper suggests an intelligent Student Actions Evaluation System using Deep Learning (iSAES-DL)for student monitoring in physical education. This model uses the deep convolution neural network for the classification of risky actions. This model further evaluates the learners’ degree of learning, retention, and achievements and suggests improvements and corrective measures. It highlights the benefits, uses, and limitations of applying deep learning techniques and IoT devices to develop learning analytics systems in the physical, educational domain. Eventually, output criteria such as comprehension, concentration, retention, and learner attainment are given a feature-by-feature analysis of the proposed methodology and traditional teaching-learning approaches. Finally, the classification algorithm is contrasted to other deep learning algorithms with an F1-score of 97.86%.
{"title":"The Capture and Evaluation System of Student Actions in Physical Education Classroom Based on Deep Learning","authors":"Li Zhang, Sudhakar Sengan, P. Manivannan","doi":"10.1142/s0219265921430258","DOIUrl":"https://doi.org/10.1142/s0219265921430258","url":null,"abstract":"Socially, politically, and morally, the world of sport is still changing. On the other hand, technology has been the most prevalent transition in the sport over the last century. Thanks to modern science, athletes can now go higher, run quicker, and, most importantly, remain healthy. Although academics, agencies, and policymakers had already urged physical education teachers to use technology in their classrooms, in many of these situations, technology is used for administrative purposes, including tracking enrolment and measuring, documenting, and reporting students’ work. Thus, this paper suggests an intelligent Student Actions Evaluation System using Deep Learning (iSAES-DL)for student monitoring in physical education. This model uses the deep convolution neural network for the classification of risky actions. This model further evaluates the learners’ degree of learning, retention, and achievements and suggests improvements and corrective measures. It highlights the benefits, uses, and limitations of applying deep learning techniques and IoT devices to develop learning analytics systems in the physical, educational domain. Eventually, output criteria such as comprehension, concentration, retention, and learner attainment are given a feature-by-feature analysis of the proposed methodology and traditional teaching-learning approaches. Finally, the classification algorithm is contrasted to other deep learning algorithms with an F1-score of 97.86%.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126474604","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921440084
Harsha Chauhan, D. Gupta, Sheifali Gupta, Soumyabrata Nayak, A. Shankar, Prabhisek Singh
Supply chain management is implementing the standards of Industry 4.0 in order to enhance the trust and safety level in the system with invention of the latest technologies. At the same time, the customers are now more focused towards the product quality. Supply chain management is the demand of the era. However, it is difficult to trace and maintain the track data throughout the process during the supply of a product. The traditional solutions were based on centralized third party solutions, where the data is inclined to various security attacks and high risk of tempering. In this paper, a solution for the management of supply of a product has been proposed which is based on IoT with an amalgamation of blockchain so as to increase the transparency of the flow during the supply of the product. The solution will help to enhance the trust as the data will be shared among all participating nodes of the network in blockchain. It also makes instant traceability of the product and this can be done by both the end of the chain. Moreover, this solution will help the consumer to check whether the product is from a reliable source or not. For the implementation and testing of smart contracts the authors have used Remix IDE, MetaMask and RinkeyBy.
{"title":"Framework for Enhancing the Traceability in Supply Chain Using Blockchain","authors":"Harsha Chauhan, D. Gupta, Sheifali Gupta, Soumyabrata Nayak, A. Shankar, Prabhisek Singh","doi":"10.1142/s0219265921440084","DOIUrl":"https://doi.org/10.1142/s0219265921440084","url":null,"abstract":"Supply chain management is implementing the standards of Industry 4.0 in order to enhance the trust and safety level in the system with invention of the latest technologies. At the same time, the customers are now more focused towards the product quality. Supply chain management is the demand of the era. However, it is difficult to trace and maintain the track data throughout the process during the supply of a product. The traditional solutions were based on centralized third party solutions, where the data is inclined to various security attacks and high risk of tempering. In this paper, a solution for the management of supply of a product has been proposed which is based on IoT with an amalgamation of blockchain so as to increase the transparency of the flow during the supply of the product. The solution will help to enhance the trust as the data will be shared among all participating nodes of the network in blockchain. It also makes instant traceability of the product and this can be done by both the end of the chain. Moreover, this solution will help the consumer to check whether the product is from a reliable source or not. For the implementation and testing of smart contracts the authors have used Remix IDE, MetaMask and RinkeyBy.","PeriodicalId":153590,"journal":{"name":"J. Interconnect. Networks","volume":"17 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113967790","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}
Pub Date : 2022-02-10DOI: 10.1142/s0219265921410371
Srinivasa Rao Pokuri, N. Devarakonda
With a steady increase in the population of Internet users, a plethora of network services have emerged on the global level. As an offshoot of this phenomenal rise in network services and their capabilities riding on the wave of internet, we are witnessing a massive risk of attacks on network security. Many security vulnerabilities are exposed and exploited by attackers, endangering the safety of massive amounts of data. To improve a network’s effectiveness, it’s critical to detect network traffic anomalies accurately and quickly. A new hybrid model that effectively detects anomalies in network services is proposed in this work. The genetic phase and NN phase represent the 2-phased approach making each one dependent on the other for weight assignment and prediction. The genetic phase generates optimal weights for classification of normal and anomaly patterns. The NN phase learns the input output relationship of network patterns employing GA in the training phase. Detection is accomplished using trained NN and it utilizes pre-processed KDD dataset containing normal and abnormal samples for training. The outcomes demonstrated that the suggested approach outperforms all other algorithms.
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