{"title":"环境污染:移动信号塔辐射的统计方法。","authors":"Prisilla Jayanthi Gandam, Muralikrishna Iyyanki","doi":"10.31661/jbpe.v0i0.2402-1728","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The Electromagnetic Field (EMF) effect is considered an alarming human health issue, dependent on the use of mobile phones. Several nationwide awareness programs on EMF Emissions & Telecom Towers were initiated by the Department of Telecom (DoT) to build a direct bridge between the number of investors and the information gap with scientific evidence. EMF interaction with humans has caused oxidative stress for brain physiological and pathological degeneration.</p><p><strong>Objective: </strong>This study aimed to investigate the EMF's influence on oxidative stress and disorders of neurodegenerative.</p><p><strong>Material and methods: </strong>This analytical study is conducted on a generalized linear model, a supervised learning approach in machine learning, to understand mobile tower radiation. The data is obtained from open sources from two different states in India.</p><p><strong>Results: </strong>Confidential Interval (CI) was obtained for measured value radiation for Andhra Pradesh in 2018-2019 as 95% CI [0.0045 to 0.0111] and for 2019-2020 as 95% CI [0.0016 to 0.0028]. Telangana -CI for Measured Value (MV) in 2018-2019 was found to be 95% CI [0.0500 to 0.0763] and 2019-2020 is 95% CI [0.0189 to 0.4345].</p><p><strong>Conclusion: </strong>Generalized Linear Models (GLM) are the best statistical model to analyze the mobile tower radiation.</p>","PeriodicalId":38035,"journal":{"name":"Journal of Biomedical Physics and Engineering","volume":"15 3","pages":"231-238"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12153470/pdf/","citationCount":"0","resultStr":"{\"title\":\"Environmental Pollution: Statistical Approach on Mobile Tower Radiation.\",\"authors\":\"Prisilla Jayanthi Gandam, Muralikrishna Iyyanki\",\"doi\":\"10.31661/jbpe.v0i0.2402-1728\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The Electromagnetic Field (EMF) effect is considered an alarming human health issue, dependent on the use of mobile phones. Several nationwide awareness programs on EMF Emissions & Telecom Towers were initiated by the Department of Telecom (DoT) to build a direct bridge between the number of investors and the information gap with scientific evidence. EMF interaction with humans has caused oxidative stress for brain physiological and pathological degeneration.</p><p><strong>Objective: </strong>This study aimed to investigate the EMF's influence on oxidative stress and disorders of neurodegenerative.</p><p><strong>Material and methods: </strong>This analytical study is conducted on a generalized linear model, a supervised learning approach in machine learning, to understand mobile tower radiation. The data is obtained from open sources from two different states in India.</p><p><strong>Results: </strong>Confidential Interval (CI) was obtained for measured value radiation for Andhra Pradesh in 2018-2019 as 95% CI [0.0045 to 0.0111] and for 2019-2020 as 95% CI [0.0016 to 0.0028]. Telangana -CI for Measured Value (MV) in 2018-2019 was found to be 95% CI [0.0500 to 0.0763] and 2019-2020 is 95% CI [0.0189 to 0.4345].</p><p><strong>Conclusion: </strong>Generalized Linear Models (GLM) are the best statistical model to analyze the mobile tower radiation.</p>\",\"PeriodicalId\":38035,\"journal\":{\"name\":\"Journal of Biomedical Physics and Engineering\",\"volume\":\"15 3\",\"pages\":\"231-238\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12153470/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomedical Physics and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31661/jbpe.v0i0.2402-1728\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Physics and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31661/jbpe.v0i0.2402-1728","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}
Environmental Pollution: Statistical Approach on Mobile Tower Radiation.
Background: The Electromagnetic Field (EMF) effect is considered an alarming human health issue, dependent on the use of mobile phones. Several nationwide awareness programs on EMF Emissions & Telecom Towers were initiated by the Department of Telecom (DoT) to build a direct bridge between the number of investors and the information gap with scientific evidence. EMF interaction with humans has caused oxidative stress for brain physiological and pathological degeneration.
Objective: This study aimed to investigate the EMF's influence on oxidative stress and disorders of neurodegenerative.
Material and methods: This analytical study is conducted on a generalized linear model, a supervised learning approach in machine learning, to understand mobile tower radiation. The data is obtained from open sources from two different states in India.
Results: Confidential Interval (CI) was obtained for measured value radiation for Andhra Pradesh in 2018-2019 as 95% CI [0.0045 to 0.0111] and for 2019-2020 as 95% CI [0.0016 to 0.0028]. Telangana -CI for Measured Value (MV) in 2018-2019 was found to be 95% CI [0.0500 to 0.0763] and 2019-2020 is 95% CI [0.0189 to 0.4345].
Conclusion: Generalized Linear Models (GLM) are the best statistical model to analyze the mobile tower radiation.
期刊介绍:
The Journal of Biomedical Physics and Engineering (JBPE) is a bimonthly peer-reviewed English-language journal that publishes high-quality basic sciences and clinical research (experimental or theoretical) broadly concerned with the relationship of physics to medicine and engineering.