Pub Date : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060575
R. Ramachandran, D. Deenakumar
A pandemic is an epidemic that spreads widely beyond national lines and has an impact on the entire planet. It produces a lot of illnesses that can be fatal. For instance, although though cancer claims many lives, the disease is not considered a pandemic because it cannot be spread readily or even be infectious. Pandemics, which meaning “everyone” in Greek, are where the word “pandemic” originates. The term “demo” refers to the populace. All people are Pan. Therefore, the idea of a “pan demo” assumes that the entire world's population will be exposed to this illness and that some of them will get sick. Sadly, an unforeseen cause has struck the world with the corona virus's growth in India in 2020 and other nations throughout the time of 2019. A research study on migrant workers is required because they have significantly impacted the socioeconomic sector. The goal of this study is to ascertain how the Covid-19epidemic has affected migrant workers' quality of life in Tiruchirappalli, Tamil Nadu. Due to the fact that this is an empirical study, the field survey method and personal interview techniques were used to collect the necessary data from the respondents. The researcher interacted with each visitor at the job site and collected the necessary data through interviews and scheduling. A total of 487 persons were included in the sample size for the investigation. Statistics were employed for this inquiry, including frequency analysis, regression, and correlation analysis. The interpretation's output is the findings and observations of the analytical study.
{"title":"Influence of the Covid-19 Pandemic on Migrant Workers' Quality of Life in Trichirappalli, Tamilnadu","authors":"R. Ramachandran, D. Deenakumar","doi":"10.1109/ICERECT56837.2022.10060575","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060575","url":null,"abstract":"A pandemic is an epidemic that spreads widely beyond national lines and has an impact on the entire planet. It produces a lot of illnesses that can be fatal. For instance, although though cancer claims many lives, the disease is not considered a pandemic because it cannot be spread readily or even be infectious. Pandemics, which meaning “everyone” in Greek, are where the word “pandemic” originates. The term “demo” refers to the populace. All people are Pan. Therefore, the idea of a “pan demo” assumes that the entire world's population will be exposed to this illness and that some of them will get sick. Sadly, an unforeseen cause has struck the world with the corona virus's growth in India in 2020 and other nations throughout the time of 2019. A research study on migrant workers is required because they have significantly impacted the socioeconomic sector. The goal of this study is to ascertain how the Covid-19epidemic has affected migrant workers' quality of life in Tiruchirappalli, Tamil Nadu. Due to the fact that this is an empirical study, the field survey method and personal interview techniques were used to collect the necessary data from the respondents. The researcher interacted with each visitor at the job site and collected the necessary data through interviews and scheduling. A total of 487 persons were included in the sample size for the investigation. Statistics were employed for this inquiry, including frequency analysis, regression, and correlation analysis. The interpretation's output is the findings and observations of the analytical study.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123550010","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}
Predictive maintenance is one of the important areas benefiting from the industry”s growth. There have been various attempts recently to use Machine Learning (ML) to improve equipment protection and maintenance, with most of those solutions relying on expert-based ML modelling. For predicting, a data-driven strategy based mostly on Random Survival Forest (RSF). In this paper the experiment analysis is conduct to determine the performances of different algorithm for the predictive maintenance of Aircraft Engine. The Different algorithm approach is shown to help and estimate the reliability feature for a selected detection of failure components inside the paper. The Random Forest Approach performs the best result with maximum explained variance and minimum absolute error. The addition of confidence bands to the Random Forest approach allows an engineer to access the accuracy of the version prediction.
{"title":"Investigation of Different Regression Models For The Predictive Maintenance of Aircraft's Engine","authors":"Om Ingole, Arnav Pande, Aayush Dongre, Dhairyashil Jadhav, Deepak Dhamecha, Harshal Daspute, Sachin Komble, Tejaswini Bhosale","doi":"10.1109/ICERECT56837.2022.10059651","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10059651","url":null,"abstract":"Predictive maintenance is one of the important areas benefiting from the industry”s growth. There have been various attempts recently to use Machine Learning (ML) to improve equipment protection and maintenance, with most of those solutions relying on expert-based ML modelling. For predicting, a data-driven strategy based mostly on Random Survival Forest (RSF). In this paper the experiment analysis is conduct to determine the performances of different algorithm for the predictive maintenance of Aircraft Engine. The Different algorithm approach is shown to help and estimate the reliability feature for a selected detection of failure components inside the paper. The Random Forest Approach performs the best result with maximum explained variance and minimum absolute error. The addition of confidence bands to the Random Forest approach allows an engineer to access the accuracy of the version prediction.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"20 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124662160","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060656
A. S., B. M, Niranjanamurthy M
When caring for special kids with neuro-development disorders, much needs to be done as there is no medical test to detect some of the special needs. The main problems faced by special kids are social skills and learning disabilities. They cannot communicate like others in the real physical world. To develop these skills a virtual imaginary world or virtual reality can be used where they will learn skills in a virtual manner. It reduces the fear of social intimacy. Augmented-Reality and Virtual-Reality are used to develop their skills and provide a platform for phobia treatments too. These technologies give the kids simple strategies that lead to awareness and acceptance of the actual physical world by stimulation in the virtual world. The use of Augmented-Reality and Virtual-Reality in the field of teaching special kids improves the concepts of understanding. Rather than learning from old or domestic teaching methods technology, where the stimulation of the actual world and the objects in it can enhance the experience of learning and understanding and implementing the knowledge or the discipline that occurred from the process in the real world without the fear of being wrong and removes the margin of the mistakes. This leads to a child having a normal and educational life. In this article proposed Feasible Virtual Reality Application for Special Kids.
{"title":"Feasible Virtual Reality Application for Special Kids","authors":"A. S., B. M, Niranjanamurthy M","doi":"10.1109/ICERECT56837.2022.10060656","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060656","url":null,"abstract":"When caring for special kids with neuro-development disorders, much needs to be done as there is no medical test to detect some of the special needs. The main problems faced by special kids are social skills and learning disabilities. They cannot communicate like others in the real physical world. To develop these skills a virtual imaginary world or virtual reality can be used where they will learn skills in a virtual manner. It reduces the fear of social intimacy. Augmented-Reality and Virtual-Reality are used to develop their skills and provide a platform for phobia treatments too. These technologies give the kids simple strategies that lead to awareness and acceptance of the actual physical world by stimulation in the virtual world. The use of Augmented-Reality and Virtual-Reality in the field of teaching special kids improves the concepts of understanding. Rather than learning from old or domestic teaching methods technology, where the stimulation of the actual world and the objects in it can enhance the experience of learning and understanding and implementing the knowledge or the discipline that occurred from the process in the real world without the fear of being wrong and removes the margin of the mistakes. This leads to a child having a normal and educational life. In this article proposed Feasible Virtual Reality Application for Special Kids.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116545648","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060811
Bijaya Kumar Sethi, P. Sarangi, Adepu Sai Aashrith
With the significant rise in medical costs, the Health Insurance Department's duty of controlling medical expenses has become increasingly vital. Traditional medical insurance settlements are paid per-service, which results in a lot of unnecessary costs. Now a day, the single-disease payment mechanism has been frequently employed to address this issue. However, there is a possibility of fraud with single-disease payments. In this work, the authors have presented a methodology for detecting the health insurance fraud entrenched block chain and Machine learning techniques like Support Vector Machine (SVM) and logistic Regression, that can automatically recognize apprehensive medical records to assure sustainable execution of single-disease payment and reduce medical insurance worker's workload. The authors have also proposed a medical record storage and management procedure based on consortium block chain to assure data security, immutability, traceability, and audit ability. The suggested system may effectively identify fraud and considerably increase the efficiency of medical insurance evaluations, as demonstrated by experiments on two real datasets from two 3A hospitals.
{"title":"Medical Insurance Fraud Detection Based on Block Chain and Machine Learning Approach","authors":"Bijaya Kumar Sethi, P. Sarangi, Adepu Sai Aashrith","doi":"10.1109/ICERECT56837.2022.10060811","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060811","url":null,"abstract":"With the significant rise in medical costs, the Health Insurance Department's duty of controlling medical expenses has become increasingly vital. Traditional medical insurance settlements are paid per-service, which results in a lot of unnecessary costs. Now a day, the single-disease payment mechanism has been frequently employed to address this issue. However, there is a possibility of fraud with single-disease payments. In this work, the authors have presented a methodology for detecting the health insurance fraud entrenched block chain and Machine learning techniques like Support Vector Machine (SVM) and logistic Regression, that can automatically recognize apprehensive medical records to assure sustainable execution of single-disease payment and reduce medical insurance worker's workload. The authors have also proposed a medical record storage and management procedure based on consortium block chain to assure data security, immutability, traceability, and audit ability. The suggested system may effectively identify fraud and considerably increase the efficiency of medical insurance evaluations, as demonstrated by experiments on two real datasets from two 3A hospitals.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"364 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123132101","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060741
B. Kavitha, K. Naveen
Lung cancer has a relatively low-down cure speed in its later stage. Lung cancer survival rates might be significantly enhanced if effective early detection could be obtained. Early lung cancer identification is crucial for human health. The suggested technique, which consists of two phases, attempts to identify lung cancer early. It Imports lung CT scans into the structure immediately, and then proceeds to the image layout step, utilizing explicit image management processes. The proposed method incorporates several advances, including image acquisition, pre-processing, binarization, thresholding, division, feature extraction, and neural organization identification. The binarization method changes matched pictures and contrasts them with edge views and, the feature extraction technique eliminates specified essential properties from the segmented images. The brain structure is constructed using the retrieved attributes, and the framework is then scanned for malignant or benign images. The proposed framework produces acceptable results, and the proposed technique has a precision of 94 percent.
{"title":"Image Acquisition and Pre-processing for Detection of Lung Cancer using Neural Network","authors":"B. Kavitha, K. Naveen","doi":"10.1109/ICERECT56837.2022.10060741","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060741","url":null,"abstract":"Lung cancer has a relatively low-down cure speed in its later stage. Lung cancer survival rates might be significantly enhanced if effective early detection could be obtained. Early lung cancer identification is crucial for human health. The suggested technique, which consists of two phases, attempts to identify lung cancer early. It Imports lung CT scans into the structure immediately, and then proceeds to the image layout step, utilizing explicit image management processes. The proposed method incorporates several advances, including image acquisition, pre-processing, binarization, thresholding, division, feature extraction, and neural organization identification. The binarization method changes matched pictures and contrasts them with edge views and, the feature extraction technique eliminates specified essential properties from the segmented images. The brain structure is constructed using the retrieved attributes, and the framework is then scanned for malignant or benign images. The proposed framework produces acceptable results, and the proposed technique has a precision of 94 percent.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130813438","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060374
Yating Liu
In view of the shortcomings of traditional interior design, such as small changes, less experience, low work efficiency and high development cost, this paper proposes an indoor display system based on artificial intelligence algorithm, analyzes the importance and value of system design, and verifies the realization algorithm of the main functions of the system. Methods According to the element type, the model file was modeled and generated by artificial intelligence algorithm. At the same time, through the development of module functions, the system roaming and interactive functions are realized Therefore, the virtual interior design system shows the overall result of the final interior design. Users can view virtual space or change its design in real time as they wish, including changing wallpaper or floor style, moving furniture or changing furniture location, deleting unsatisfied furniture, adding interesting furniture, etc. Conclusion Virtual interior decoration system can improve user experience and satisfaction, improve the efficiency of design companies, and reduce design costs.
{"title":"Application of Artificial Intelligence Algorithm in Indoor Virtual Display System","authors":"Yating Liu","doi":"10.1109/ICERECT56837.2022.10060374","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060374","url":null,"abstract":"In view of the shortcomings of traditional interior design, such as small changes, less experience, low work efficiency and high development cost, this paper proposes an indoor display system based on artificial intelligence algorithm, analyzes the importance and value of system design, and verifies the realization algorithm of the main functions of the system. Methods According to the element type, the model file was modeled and generated by artificial intelligence algorithm. At the same time, through the development of module functions, the system roaming and interactive functions are realized Therefore, the virtual interior design system shows the overall result of the final interior design. Users can view virtual space or change its design in real time as they wish, including changing wallpaper or floor style, moving furniture or changing furniture location, deleting unsatisfied furniture, adding interesting furniture, etc. Conclusion Virtual interior decoration system can improve user experience and satisfaction, improve the efficiency of design companies, and reduce design costs.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896164","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060522
Geetha Rani E, Tanuep Bellam, Mounika E, B. P., Gopala Krishnan C, Anusha D
As a result of many technological developments and growing usage of artificial intelligence in our daily routines, the number of autonomous and self-driving vehicles has expanded dramatically. To be effective and efficient, autonomous cars must be able to recognize and interpret a variety of traffic signs and take appropriate responses. A technology known as Traffic Sign Recognition can be used to determine a large number of different traffic signs. Traffic Sign Recognition is a technique that enables self-driving or autonomous vehicles to recognize traffic signs on the road. We must classify the images into their appropriate categories or groupings once they have been recognized. We accomplish this by creating a Convolutional Neural Network model. We must apply a discipline of artificial intelligence known as computer vision to derive information from the images acquired and recognized by the Traffic Sign Recognition and make recommendations based on that knowledge. In our paper, we'll use a Convolutional Neural Network model to create distinct indications in the image that may be sorted into several categories. As a result, the system can read and understand traffic signs, which is a crucial duty in the creation and improvement of autonomous vehicles. Because this would be used in a real-time setting, we have included blurry images in our dataset to emulate real-time capturing scenarios like as when the vehicle is moving or when direct light is shining on the subject.
{"title":"A Practical Approach of Recognizing and Detecting Traffic Signs using Deep Neural Network Model","authors":"Geetha Rani E, Tanuep Bellam, Mounika E, B. P., Gopala Krishnan C, Anusha D","doi":"10.1109/ICERECT56837.2022.10060522","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060522","url":null,"abstract":"As a result of many technological developments and growing usage of artificial intelligence in our daily routines, the number of autonomous and self-driving vehicles has expanded dramatically. To be effective and efficient, autonomous cars must be able to recognize and interpret a variety of traffic signs and take appropriate responses. A technology known as Traffic Sign Recognition can be used to determine a large number of different traffic signs. Traffic Sign Recognition is a technique that enables self-driving or autonomous vehicles to recognize traffic signs on the road. We must classify the images into their appropriate categories or groupings once they have been recognized. We accomplish this by creating a Convolutional Neural Network model. We must apply a discipline of artificial intelligence known as computer vision to derive information from the images acquired and recognized by the Traffic Sign Recognition and make recommendations based on that knowledge. In our paper, we'll use a Convolutional Neural Network model to create distinct indications in the image that may be sorted into several categories. As a result, the system can read and understand traffic signs, which is a crucial duty in the creation and improvement of autonomous vehicles. Because this would be used in a real-time setting, we have included blurry images in our dataset to emulate real-time capturing scenarios like as when the vehicle is moving or when direct light is shining on the subject.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134282582","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}
There is a significant increase in the usage of DFIG-based wind energy conversion systems due its advantages like its flexible speed operation, fractional rating power converters, and its reactive power sustenance. However, a wind farm with a doubly fed induction generator which is incorporated to the transmission line having a series compensation may give rise to the Sub Synchronous Resonance (SSR) issue. In a wind farm with series compensation, the SSR phenomena implies the potential concerns. The Sub synchronous control interaction issues have been caused due to the increased use of series compensation in DFIG-based wind farms. For SSCI, the non-periodic energy exchange amongst the network side and the generator side is the most significant cause. In this work, an investigation is performed on the applications of Gate-Controlled Series Capacitor (GCSC) and Thyristor Controlled Series Capacitor (TCSC), which is a series linked FACTS device which can be used for series compensation in fixed speed wind turbine generator systems. The transmission line series impedance can be quickly controlled by the GCSC and used for SSR dampening. To validate the findings, the simulations studies is performed using MATLAB/SIMULINK. Both GCSC and TCSC are capable successfully damping the SSR in wind farms and provide the better quality of power for the consumers.
{"title":"GCSC and TCSC Implementation in DFIG Based Wind Farms to Mitigate Sub Synchronous Resonance","authors":"Chethan Hiremarali Ramalingegowda, Mageshvaran Rudramoorthy","doi":"10.1109/ICERECT56837.2022.10060155","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060155","url":null,"abstract":"There is a significant increase in the usage of DFIG-based wind energy conversion systems due its advantages like its flexible speed operation, fractional rating power converters, and its reactive power sustenance. However, a wind farm with a doubly fed induction generator which is incorporated to the transmission line having a series compensation may give rise to the Sub Synchronous Resonance (SSR) issue. In a wind farm with series compensation, the SSR phenomena implies the potential concerns. The Sub synchronous control interaction issues have been caused due to the increased use of series compensation in DFIG-based wind farms. For SSCI, the non-periodic energy exchange amongst the network side and the generator side is the most significant cause. In this work, an investigation is performed on the applications of Gate-Controlled Series Capacitor (GCSC) and Thyristor Controlled Series Capacitor (TCSC), which is a series linked FACTS device which can be used for series compensation in fixed speed wind turbine generator systems. The transmission line series impedance can be quickly controlled by the GCSC and used for SSR dampening. To validate the findings, the simulations studies is performed using MATLAB/SIMULINK. Both GCSC and TCSC are capable successfully damping the SSR in wind farms and provide the better quality of power for the consumers.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133713006","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10059838
Yuhua Wei
The new generation of information technology represented by 5g + AI has changed China's education and teaching methods and brought new technological changes to education and teaching. The “cloud-network-side-end” integrated campus intelligent system based on artificial intelligence has the advantages of providing personalized services, realizing the interaction and integration of information, and enhancing the humanization of services. However, at present, many colleges and universities have problems such as backward technology, low degree of integration of information technology and education, and low network security in the process of smart campus construction. Therefore, the smart campus platform system based on artificial intelligence technology should include six layers: perception layer, network layer, data layer, application layer, service layer and technical specification layer, covering education and teaching, educational administration, life and entertainment, etc. application services. In order to give full play to the advantages of 5G+AI in the “cloud-network-edge-device” integrated campus intelligent system, colleges and universities should strengthen the construction of campus infrastructure, speed up the reform of classroom teaching, and attach importance to the construction of information security systems, so that smart campuses can be Provide better service experience for teachers and students.
{"title":"Research on the Construction of “Cloud-network-edge-device” Integrated Campus Intelligent System Based on 5G+AI","authors":"Yuhua Wei","doi":"10.1109/ICERECT56837.2022.10059838","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10059838","url":null,"abstract":"The new generation of information technology represented by 5g + AI has changed China's education and teaching methods and brought new technological changes to education and teaching. The “cloud-network-side-end” integrated campus intelligent system based on artificial intelligence has the advantages of providing personalized services, realizing the interaction and integration of information, and enhancing the humanization of services. However, at present, many colleges and universities have problems such as backward technology, low degree of integration of information technology and education, and low network security in the process of smart campus construction. Therefore, the smart campus platform system based on artificial intelligence technology should include six layers: perception layer, network layer, data layer, application layer, service layer and technical specification layer, covering education and teaching, educational administration, life and entertainment, etc. application services. In order to give full play to the advantages of 5G+AI in the “cloud-network-edge-device” integrated campus intelligent system, colleges and universities should strengthen the construction of campus infrastructure, speed up the reform of classroom teaching, and attach importance to the construction of information security systems, so that smart campuses can be Provide better service experience for teachers and students.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256356","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 : 2022-12-26DOI: 10.1109/ICERECT56837.2022.10060182
G. Vijayakumar, P. Mageshwari, A. Vijayalakshmi
The enrichment of predominant properties of materials by the mixture of two metal oxides has increased popularity such as to intensify in terms of fraction of atoms with high surface area that primarily relies on the shape, size, morphology and composition. Synthesized BaO-MnO metal nanocomposite exhibits crystalline nature which is exemplified by powder XRD characterization. The diffraction peaks with reflections (111)*, (110)*, (200) * belong to the tetragonal BaO structure and the peak reflections corresponding to planes (111) #, (220) #, (311) # belong to the cubic structure of MnO. The groupings of barium oxide (BaO) and manganese oxide (MnO) are chosen for their unique non-linear optic, magnetic and electric properties for the applications in rechargeable batteries, laser technology, wastewater treatment, etc. The metal nanocomposites' structure, morphology, dielectric, and optical characteristics were investigated, and the results were carefully examined. FTIR characterization has confirmed the existence of the functional group.
{"title":"Experimental and Theoretical Investigations on Structural, Morphological, Optical and Dielectric behavior of novel BaO-MnO Metal Nanocomposites","authors":"G. Vijayakumar, P. Mageshwari, A. Vijayalakshmi","doi":"10.1109/ICERECT56837.2022.10060182","DOIUrl":"https://doi.org/10.1109/ICERECT56837.2022.10060182","url":null,"abstract":"The enrichment of predominant properties of materials by the mixture of two metal oxides has increased popularity such as to intensify in terms of fraction of atoms with high surface area that primarily relies on the shape, size, morphology and composition. Synthesized BaO-MnO metal nanocomposite exhibits crystalline nature which is exemplified by powder XRD characterization. The diffraction peaks with reflections (111)*, (110)*, (200) * belong to the tetragonal BaO structure and the peak reflections corresponding to planes (111) #, (220) #, (311) # belong to the cubic structure of MnO. The groupings of barium oxide (BaO) and manganese oxide (MnO) are chosen for their unique non-linear optic, magnetic and electric properties for the applications in rechargeable batteries, laser technology, wastewater treatment, etc. The metal nanocomposites' structure, morphology, dielectric, and optical characteristics were investigated, and the results were carefully examined. FTIR characterization has confirmed the existence of the functional group.","PeriodicalId":205485,"journal":{"name":"2022 Fourth International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115070721","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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