Now a days Noise pollution is largest unwanted sound in the industrial sector. The Global population has grown in different decades Such as 1980-2000, 2000-2024. The annual population increase during the preceding decade about 2 percent. Due to increase in population, urbanization and industrialization happening and because of this noise pollution is increasing. In the world mostly noise generated from industrial sector. This noise create negative impact on surrounding environment such as (human, vegetation and animals) health. Effect of exposure to high noise level on workers and their performance of work and calmness. This research work was conducted to investigate the use of sound absorbing various combinations of green material for industrial noise attenuation to give effective solution for industrial noise problem. The specimen was prepared using different combinations with binding material cement (Adhesive). Noise reduction coefficients of specimens were calculated by using impedance tube system experimental setup. Effectiveness of sound absorbing natural materials for industrial noise attenuation is discussed in this paper. Keywords — Sound absorbing of green material, noise level meter, Impedance tube system, Stainless steel. Cement
{"title":"Techno-Economical Study of Innovative Construction Material for Industrial Noise Abatement","authors":"Ijsrem Journal","doi":"10.55041/ijsrem37032","DOIUrl":"https://doi.org/10.55041/ijsrem37032","url":null,"abstract":"Now a days Noise pollution is largest unwanted sound in the industrial sector. The Global population has grown in different decades Such as 1980-2000, 2000-2024. The annual population increase during the preceding decade about 2 percent. Due to increase in population, urbanization and industrialization happening and because of this noise pollution is increasing. In the world mostly noise generated from industrial sector. This noise create negative impact on surrounding environment such as (human, vegetation and animals) health. Effect of exposure to high noise level on workers and their performance of work and calmness. This research work was conducted to investigate the use of sound absorbing various combinations of green material for industrial noise attenuation to give effective solution for industrial noise problem. The specimen was prepared using different combinations with binding material cement (Adhesive). Noise reduction coefficients of specimens were calculated by using impedance tube system experimental setup. Effectiveness of sound absorbing natural materials for industrial noise attenuation is discussed in this paper. Keywords — Sound absorbing of green material, noise level meter, Impedance tube system, Stainless steel. Cement","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"12 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920602","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 aim of the project work is to treat the landfill leachate before disposal. The necessity for landfill leachate treatment is a requisite to reduce the environmental related to impact related to municipal solid waste land fill. If leachate is directly disposed into environment it creates serious problems on the surrounding soil, ground water aquifers and nearby surface water. Therefore great attention has been directed towards new techniques based on physico- chemical process, and heavy metals removal using low cost materials as filter media with down flow reactor. Leachate generation is a major problem for municipal solid waste (MSW) landfills and causes significant threat to surface water and groundwater. Leachate can be defined as a liquid that passes through a landfill and has extracted dissolved and suspended matter from it. Leachate results from precipitation entering the landfill from moisture that exists in the waste when it is composed. Different consider while deciding for an appropriate treatment process. This paper presents the results of the analyses of leachate treatment from the solid waste land fill. Key Words: : Leachate, physico-chemical process, landfill, precipitation, solid waste, Municipal Solid Waste (MSW).
{"title":"Experimental Investigation of Leachate Treatment Using Low-Cost Adsorbents","authors":"R. A, S. T","doi":"10.55041/ijsrem37021","DOIUrl":"https://doi.org/10.55041/ijsrem37021","url":null,"abstract":"The aim of the project work is to treat the landfill leachate before disposal. The necessity for landfill leachate treatment is a requisite to reduce the environmental related to impact related to municipal solid waste land fill. If leachate is directly disposed into environment it creates serious problems on the surrounding soil, ground water aquifers and nearby surface water. Therefore great attention has been directed towards new techniques based on physico- chemical process, and heavy metals removal using low cost materials as filter media with down flow reactor. Leachate generation is a major problem for municipal solid waste (MSW) landfills and causes significant threat to surface water and groundwater. Leachate can be defined as a liquid that passes through a landfill and has extracted dissolved and suspended matter from it. Leachate results from precipitation entering the landfill from moisture that exists in the waste when it is composed. Different consider while deciding for an appropriate treatment process. This paper presents the results of the analyses of leachate treatment from the solid waste land fill. Key Words: : Leachate, physico-chemical process, landfill, precipitation, solid waste, Municipal Solid Waste (MSW).","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"2 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920060","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}
This research paper delves into the inherent vulnerabilities and potential threats posed by large language models (LLMs), focusing on their implications across diverse applications such as natural language processing and data privacy. The study aims to identify and analyze these risks comprehensively, emphasizing the importance of mitigating strategies to prevent exploitation and misuse in LLM deployments. In recent years, LLMs have revolutionized fields like automated content generation, sentiment analysis, and conversational agents, yet their immense capabilities also raise significant security concerns. Vulnerabilities such as bias amplification, adversarial attacks, and unintended data leakage can undermine trust and compromise user privacy. Through a systematic examination of these challenges, this paper proposes safeguarding measures crucial for responsibly harnessing the potential of LLMs while minimizing associated risks. It underscores the necessity of rigorous security protocols, including robust encryption methods, enhanced authentication mechanisms, and continuous monitoring frameworks. Furthermore, the research discusses regulatory implications and ethical considerations surrounding LLM usage, advocating for transparency, accountability, and stakeholder engagement in policy- making and deployment practices. By synthesizing insights from current literature and real-world case studies, this study provides a comprehensive framework for stakeholders—developers, policymakers, and users—to navigate the complex landscape of LLM security effectively. Ultimately, this research aims to inform future advancements in LLM technology, ensuring its safe and beneficial integration into various domains while mitigating potential risks to individuals and society as a whole. Keywords— Adversarial attacks on LLMs, Bias in LLMs, Data privacy in LLMs, Ethical considerations LLMs, Exploitation of LLMs, Large Language Models (LLMs), Misuse of LLMs, Mitigation strategies for LLMs, Natural Language Processing (NLP), Regulatory frameworks LLMs, Responsible deployment of LLMs, Risks of LLMs, Security implications of LLMs, Threats to LLMs, Vulnerabilities in LLMs.
{"title":"Exploring Vulnerabilities and Threats in Large Language Models: Safeguarding Against Exploitation and Misuse","authors":"Mr. Aarush Varma, Dr. Mohan Kshirsagar","doi":"10.55041/ijsrem36608","DOIUrl":"https://doi.org/10.55041/ijsrem36608","url":null,"abstract":"This research paper delves into the inherent vulnerabilities and potential threats posed by large language models (LLMs), focusing on their implications across diverse applications such as natural language processing and data privacy. The study aims to identify and analyze these risks comprehensively, emphasizing the importance of mitigating strategies to prevent exploitation and misuse in LLM deployments. In recent years, LLMs have revolutionized fields like automated content generation, sentiment analysis, and conversational agents, yet their immense capabilities also raise significant security concerns. Vulnerabilities such as bias amplification, adversarial attacks, and unintended data leakage can undermine trust and compromise user privacy. Through a systematic examination of these challenges, this paper proposes safeguarding measures crucial for responsibly harnessing the potential of LLMs while minimizing associated risks. It underscores the necessity of rigorous security protocols, including robust encryption methods, enhanced authentication mechanisms, and continuous monitoring frameworks. Furthermore, the research discusses regulatory implications and ethical considerations surrounding LLM usage, advocating for transparency, accountability, and stakeholder engagement in policy- making and deployment practices. By synthesizing insights from current literature and real-world case studies, this study provides a comprehensive framework for stakeholders—developers, policymakers, and users—to navigate the complex landscape of LLM security effectively. Ultimately, this research aims to inform future advancements in LLM technology, ensuring its safe and beneficial integration into various domains while mitigating potential risks to individuals and society as a whole. Keywords— Adversarial attacks on LLMs, Bias in LLMs, Data privacy in LLMs, Ethical considerations LLMs, Exploitation of LLMs, Large Language Models (LLMs), Misuse of LLMs, Mitigation strategies for LLMs, Natural Language Processing (NLP), Regulatory frameworks LLMs, Responsible deployment of LLMs, Risks of LLMs, Security implications of LLMs, Threats to LLMs, Vulnerabilities in LLMs.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141919856","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}
This research paper delves into the inherent vulnerabilities and potential threats posed by large language models (LLMs), focusing on their implications across diverse applications such as natural language processing and data privacy. The study aims to identify and analyze these risks comprehensively, emphasizing the importance of mitigating strategies to prevent exploitation and misuse in LLM deployments. In recent years, LLMs have revolutionized fields like automated content generation, sentiment analysis, and conversational agents, yet their immense capabilities also raise significant security concerns. Vulnerabilities such as bias amplification, adversarial attacks, and unintended data leakage can undermine trust and compromise user privacy. Through a systematic examination of these challenges, this paper proposes safeguarding measures crucial for responsibly harnessing the potential of LLMs while minimizing associated risks. It underscores the necessity of rigorous security protocols, including robust encryption methods, enhanced authentication mechanisms, and continuous monitoring frameworks. Furthermore, the research discusses regulatory implications and ethical considerations surrounding LLM usage, advocating for transparency, accountability, and stakeholder engagement in policy- making and deployment practices. By synthesizing insights from current literature and real-world case studies, this study provides a comprehensive framework for stakeholders—developers, policymakers, and users—to navigate the complex landscape of LLM security effectively. Ultimately, this research aims to inform future advancements in LLM technology, ensuring its safe and beneficial integration into various domains while mitigating potential risks to individuals and society as a whole. Keywords— Adversarial attacks on LLMs, Bias in LLMs, Data privacy in LLMs, Ethical considerations LLMs, Exploitation of LLMs, Large Language Models (LLMs), Misuse of LLMs, Mitigation strategies for LLMs, Natural Language Processing (NLP), Regulatory frameworks LLMs, Responsible deployment of LLMs, Risks of LLMs, Security implications of LLMs, Threats to LLMs, Vulnerabilities in LLMs.
{"title":"Exploring Vulnerabilities and Threats in Large Language Models: Safeguarding Against Exploitation and Misuse","authors":"Mr. Aarush Varma, Dr. Mohan Kshirsagar","doi":"10.55041/ijsrem36608","DOIUrl":"https://doi.org/10.55041/ijsrem36608","url":null,"abstract":"This research paper delves into the inherent vulnerabilities and potential threats posed by large language models (LLMs), focusing on their implications across diverse applications such as natural language processing and data privacy. The study aims to identify and analyze these risks comprehensively, emphasizing the importance of mitigating strategies to prevent exploitation and misuse in LLM deployments. In recent years, LLMs have revolutionized fields like automated content generation, sentiment analysis, and conversational agents, yet their immense capabilities also raise significant security concerns. Vulnerabilities such as bias amplification, adversarial attacks, and unintended data leakage can undermine trust and compromise user privacy. Through a systematic examination of these challenges, this paper proposes safeguarding measures crucial for responsibly harnessing the potential of LLMs while minimizing associated risks. It underscores the necessity of rigorous security protocols, including robust encryption methods, enhanced authentication mechanisms, and continuous monitoring frameworks. Furthermore, the research discusses regulatory implications and ethical considerations surrounding LLM usage, advocating for transparency, accountability, and stakeholder engagement in policy- making and deployment practices. By synthesizing insights from current literature and real-world case studies, this study provides a comprehensive framework for stakeholders—developers, policymakers, and users—to navigate the complex landscape of LLM security effectively. Ultimately, this research aims to inform future advancements in LLM technology, ensuring its safe and beneficial integration into various domains while mitigating potential risks to individuals and society as a whole. Keywords— Adversarial attacks on LLMs, Bias in LLMs, Data privacy in LLMs, Ethical considerations LLMs, Exploitation of LLMs, Large Language Models (LLMs), Misuse of LLMs, Mitigation strategies for LLMs, Natural Language Processing (NLP), Regulatory frameworks LLMs, Responsible deployment of LLMs, Risks of LLMs, Security implications of LLMs, Threats to LLMs, Vulnerabilities in LLMs.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"2 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141919402","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 study of multidimensional alien megastructures offers an intriguing junction of sophisticated astrophysical ideas with the quest for extraterrestrial intelligence. This research examines the theoretical underpinnings, detection methods, and prospective consequences of megastructures like as Dyson spheres, Ringworlds, and stellar engines for exoplanetary habitability. We study the feasibility and observable signatures of higher- dimensional structures using notions from string theory and M-theory. Initial simulations of a 4D Dyson Sphere, 4D Ring World, and higher-dimensional stellar engines interacting with chosen exoplanets show encouraging findings for energy collection efficiency, structural stability, and habitability potential. Our findings indicate that sophisticated civilizations may use higher-dimensional technology to maximize energy management and habitat construction, opening up new pathways for identifying techno signatures and broadening our understanding of the universe. Future study should concentrate on creating more advanced models, enhancing detecting technologies, and investigating the real engineering issues that come with these ambitious constructions.
对多维外星巨型结构的研究为复杂的天体物理学思想和对外星智慧的探索提供了一个引人入胜的交汇点。这项研究探讨了戴森球、环世界和恒星引擎等巨型结构的理论基础、探测方法和对系外行星宜居性的预期影响。我们利用弦理论和 M 理论的概念研究了高维结构的可行性和可观测特征。对4维戴森球、4维环世界和高维恒星引擎与所选系外行星的相互作用进行的初步模拟显示，在能量收集效率、结构稳定性和宜居潜力方面都有令人鼓舞的发现。我们的研究结果表明，先进文明可能会使用高维技术来最大限度地管理能源和建造栖息地，这为识别技术特征和拓宽我们对宇宙的认识开辟了新的途径。未来的研究应集中在创建更先进的模型、提高探测技术以及调查这些雄心勃勃的建筑所带来的实际工程问题上。
{"title":"Multidimensional Alien Mega Structures and their Implications for Exoplanetary Habitability","authors":"Chirag UllasKumar Pandya","doi":"10.55041/ijsrem37023","DOIUrl":"https://doi.org/10.55041/ijsrem37023","url":null,"abstract":"The study of multidimensional alien megastructures offers an intriguing junction of sophisticated astrophysical ideas with the quest for extraterrestrial intelligence. This research examines the theoretical underpinnings, detection methods, and prospective consequences of megastructures like as Dyson spheres, Ringworlds, and stellar engines for exoplanetary habitability. We study the feasibility and observable signatures of higher- dimensional structures using notions from string theory and M-theory. Initial simulations of a 4D Dyson Sphere, 4D Ring World, and higher-dimensional stellar engines interacting with chosen exoplanets show encouraging findings for energy collection efficiency, structural stability, and habitability potential. Our findings indicate that sophisticated civilizations may use higher-dimensional technology to maximize energy management and habitat construction, opening up new pathways for identifying techno signatures and broadening our understanding of the universe. Future study should concentrate on creating more advanced models, enhancing detecting technologies, and investigating the real engineering issues that come with these ambitious constructions.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"12 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920293","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}
Shruthi C.K., Balaji M, Arjun Sathish B.K, Dinesh S
Exact correlation of contactless 2D unique finger impression pictures with contact-based fingerprints is basic for the achievement of developing contactless 2D unique finger impression innovations, which offer more sterile and distortion free procurement of unique finger impression features. Convolutional neural systems (CNN) have demonstrated comment capable capacities in biometrics acknowledgment. Be that as it may, there has been nearly nil endeavor to coordinate unique mark pictures utilizing CNN- based methodologies. This paper builds up a CNN- based system to precisely coordinate contactless and contact-based unique mark pictures. Our structure right off the bat prepares a multi-Siamese CNN utilizing unique finger impression details, individual edge guide and particular district of edge outline. Key Words: Biometric, samples.
{"title":"BANK TRANSACTION USING IRIS AND BIOMETRIC","authors":"Shruthi C.K., Balaji M, Arjun Sathish B.K, Dinesh S","doi":"10.55041/ijsrem37037","DOIUrl":"https://doi.org/10.55041/ijsrem37037","url":null,"abstract":"Exact correlation of contactless 2D unique finger impression pictures with contact-based fingerprints is basic for the achievement of developing contactless 2D unique finger impression innovations, which offer more sterile and distortion free procurement of unique finger impression features. Convolutional neural systems (CNN) have demonstrated comment capable capacities in biometrics acknowledgment. Be that as it may, there has been nearly nil endeavor to coordinate unique mark pictures utilizing CNN- based methodologies. This paper builds up a CNN- based system to precisely coordinate contactless and contact-based unique mark pictures. Our structure right off the bat prepares a multi-Siamese CNN utilizing unique finger impression details, individual edge guide and particular district of edge outline. Key Words: Biometric, samples.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"6 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141919924","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 rapid advancement of optical communication networks necessitates innovative approaches to address challenges in fault tolerance and network resilience. Here focuses on enhancing the fault tolerance and resilience of Reconfigurable Elastic Optical Networks (REONs) by integrating Spike-Timing-Dependent Plasticity (STDP) mechanisms, a biologically inspired learning rule, with neuromorphic computing techniques. The research highlights the flexibility of REONs in dynamically reallocating resources and reconfiguring network paths to manage varying traffic loads and unexpected faults. The traditional fault management methods in optical networks, which often rely on predefined backup paths, are limited by delays and suboptimal performance. By contrast, STDP offers a novel approach that allows the network to adapt in real-time through continuous learning from past experiences. This adaptive capability makes REONs more robust and efficient, ensuring minimized downtime and improved overall performance. The study concludes that STDP-based mechanisms can significantly enhance the adaptability and fault tolerance of REONs, making them well-suited for dynamic and complex network environments. Future research could explore the scalability of these mechanisms in larger networks, their integration with other neuromorphic systems, and their application in real-world scenarios Key Words: REONs, STDP, Fault tolerance, Network resilience, Neuromorphic computing
{"title":"Fault Tolerance and Resilience in REONs through STDP Mechanisms","authors":"Avadha Bihari, Ashutosh Kumar Singh, Chandan Chandan","doi":"10.55041/ijsrem37030","DOIUrl":"https://doi.org/10.55041/ijsrem37030","url":null,"abstract":"The rapid advancement of optical communication networks necessitates innovative approaches to address challenges in fault tolerance and network resilience. Here focuses on enhancing the fault tolerance and resilience of Reconfigurable Elastic Optical Networks (REONs) by integrating Spike-Timing-Dependent Plasticity (STDP) mechanisms, a biologically inspired learning rule, with neuromorphic computing techniques. The research highlights the flexibility of REONs in dynamically reallocating resources and reconfiguring network paths to manage varying traffic loads and unexpected faults. The traditional fault management methods in optical networks, which often rely on predefined backup paths, are limited by delays and suboptimal performance. By contrast, STDP offers a novel approach that allows the network to adapt in real-time through continuous learning from past experiences. This adaptive capability makes REONs more robust and efficient, ensuring minimized downtime and improved overall performance. The study concludes that STDP-based mechanisms can significantly enhance the adaptability and fault tolerance of REONs, making them well-suited for dynamic and complex network environments. Future research could explore the scalability of these mechanisms in larger networks, their integration with other neuromorphic systems, and their application in real-world scenarios Key Words: REONs, STDP, Fault tolerance, Network resilience, Neuromorphic computing","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921081","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 real danger of accidental discovery of safety and order. In this paper, we propose the use of YOLOv8 for accident-based vision, with embedded insights and machine learning State-of-the-art Acknowledgment Question Our algorithm communicates real-time flight video from the active camera to identify them accurately Classified and Accident. We demonstrate a comprehensive approach to improve YOLOv8 performance using data sets annotated with crash images. Through comparative analysis with existing methods, we confirm the uniqueness of our vision-based algorithm in terms of speed, accuracy, and performance. Our insights help improve accident management, provide appropriate planning to improve road safety, and potentially reduce the impact of accidents on the road. Index Terms— Road Accidents, Accident Detection, Computer Vision, Machine Learning, Deep Learning, CNN Classifier, Real- time Detection, Emergency Alerting, Intelligent Transportation Systems.
{"title":"Vision based Accident Detection System Using AI ML and Yolov8 Algorithms","authors":"Prof GAYATHRI R","doi":"10.55041/ijsrem37033","DOIUrl":"https://doi.org/10.55041/ijsrem37033","url":null,"abstract":"There is a real danger of accidental discovery of safety and order. In this paper, we propose the use of YOLOv8 for accident-based vision, with embedded insights and machine learning State-of-the-art Acknowledgment Question Our algorithm communicates real-time flight video from the active camera to identify them accurately Classified and Accident. We demonstrate a comprehensive approach to improve YOLOv8 performance using data sets annotated with crash images. Through comparative analysis with existing methods, we confirm the uniqueness of our vision-based algorithm in terms of speed, accuracy, and performance. Our insights help improve accident management, provide appropriate planning to improve road safety, and potentially reduce the impact of accidents on the road. Index Terms— Road Accidents, Accident Detection, Computer Vision, Machine Learning, Deep Learning, CNN Classifier, Real- time Detection, Emergency Alerting, Intelligent Transportation Systems.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"7 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141921418","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}
Lovedeep Kaur, Dr. Amardeep Singh, Dr. Navdeep Kanwal
Abstract Thunderstorm is a major threat to life. In India it is a major disaster which causes loss of life and property every year. It is a meteorological phenomenon occurs in different parts of India which includes heavy rainfall, strong wind, hailstorm, dust storm or lightning. The earlier prediction of thunderstorms is crucial for public safety and awareness. Thunderstorm prediction is essential for public safety that’s why precision and accuracy in predicting thunderstorms is very important. Thunderstorm is a phenomenon which occurs due to formation of convection cells and the lifetime of one convection cell is less than an hour so nowcasting or short term forecasting is recommended for thunderstorms in which the model predicts the initiation, development and direction of thunderstorms sub-hourly. Indian Meteorological department uses satellites that are INSAT-3DR (74°E), INSAT-3D (84°E) & Kalpana-1 (72.4°E) operationally for forecasting. Approximately 200 Agro-Automated Weather Station (Agro- AWS), 806 Automatic weather stations, 1382 Automatic Rain gauges, 83 lightning sensors along with 63 Pilot balloon upper air observation stations serve as the backbone of weather observation services of IMD throughout the country. In addition IMD has 39 Doppler Weather Radars (DWRs) well distributed across the country to monitor severe weather events. Due to advancement in technology, the thunderstorm nowcasting techniques also evolved. Now a days , radar based techniques like TITAN (Thunderstorm Identification, Tracking and Nowcasting), satellite based techniques, Numerical weather prediction, machine learning and deep learning techniques play a vital role in nowcasting. The study also discuss about the challenges faced by meteorologists during thunderstorm nowcasting. Key Words: Thunderstorm, Weather Prediction, Nowcasting
{"title":"Thunderstorm Nowcasting in India: A Survey","authors":"Lovedeep Kaur, Dr. Amardeep Singh, Dr. Navdeep Kanwal","doi":"10.55041/ijsrem37026","DOIUrl":"https://doi.org/10.55041/ijsrem37026","url":null,"abstract":"Abstract Thunderstorm is a major threat to life. In India it is a major disaster which causes loss of life and property every year. It is a meteorological phenomenon occurs in different parts of India which includes heavy rainfall, strong wind, hailstorm, dust storm or lightning. The earlier prediction of thunderstorms is crucial for public safety and awareness. Thunderstorm prediction is essential for public safety that’s why precision and accuracy in predicting thunderstorms is very important. Thunderstorm is a phenomenon which occurs due to formation of convection cells and the lifetime of one convection cell is less than an hour so nowcasting or short term forecasting is recommended for thunderstorms in which the model predicts the initiation, development and direction of thunderstorms sub-hourly. Indian Meteorological department uses satellites that are INSAT-3DR (74°E), INSAT-3D (84°E) & Kalpana-1 (72.4°E) operationally for forecasting. Approximately 200 Agro-Automated Weather Station (Agro- AWS), 806 Automatic weather stations, 1382 Automatic Rain gauges, 83 lightning sensors along with 63 Pilot balloon upper air observation stations serve as the backbone of weather observation services of IMD throughout the country. In addition IMD has 39 Doppler Weather Radars (DWRs) well distributed across the country to monitor severe weather events. Due to advancement in technology, the thunderstorm nowcasting techniques also evolved. Now a days , radar based techniques like TITAN (Thunderstorm Identification, Tracking and Nowcasting), satellite based techniques, Numerical weather prediction, machine learning and deep learning techniques play a vital role in nowcasting. The study also discuss about the challenges faced by meteorologists during thunderstorm nowcasting. Key Words: Thunderstorm, Weather Prediction, Nowcasting","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"22 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920432","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}
Since the development of remote applications and benefit, the request for a secure and quick information exchange association requires unused innovation arrangements competent to guarantee the finest countermeasure against security assaults, it is one of the foremost promising unused remote communication innovation, due to the plausibility of utilizing natural counterfeit lights as information exchange channel in free- space. The broadcast nature of VLC makes it fundamental to consider the security of fundamental transmissions. Physical layer information communication and security beneath the channel has ended up a raising concern for communication analysts and due to the victory of physical layer security (PLS) in making strides the security of radio-frequency (RF) remote systems, expanding such PLS techniques to VLC frameworks has been of incredible intrigued. By analysing some cases of the conceivable busybody dangers that can happen in these frameworks, this offers novel bits of knowledge into the vulnerabilities of state-of-the-art PLS plans for VLC frameworks, counting distinctive channel models, input disseminations, arrange arrangements, precoding/signalling techniques, and mystery capacity and data rates and beneath VLC the tall level security and security overhauling arrangements are educated and moderated a period. Key Words: Visible Light, Physical layer security, Multi User, Spread-spectrum, security performance.
{"title":"Security Enhancement in Optical Wireless Visible Light Communication","authors":"Naresh Kumar Meena, Ashutosh Kumar Singh, Chandan Kumar","doi":"10.55041/ijsrem37035","DOIUrl":"https://doi.org/10.55041/ijsrem37035","url":null,"abstract":"Since the development of remote applications and benefit, the request for a secure and quick information exchange association requires unused innovation arrangements competent to guarantee the finest countermeasure against security assaults, it is one of the foremost promising unused remote communication innovation, due to the plausibility of utilizing natural counterfeit lights as information exchange channel in free- space. The broadcast nature of VLC makes it fundamental to consider the security of fundamental transmissions. Physical layer information communication and security beneath the channel has ended up a raising concern for communication analysts and due to the victory of physical layer security (PLS) in making strides the security of radio-frequency (RF) remote systems, expanding such PLS techniques to VLC frameworks has been of incredible intrigued. By analysing some cases of the conceivable busybody dangers that can happen in these frameworks, this offers novel bits of knowledge into the vulnerabilities of state-of-the-art PLS plans for VLC frameworks, counting distinctive channel models, input disseminations, arrange arrangements, precoding/signalling techniques, and mystery capacity and data rates and beneath VLC the tall level security and security overhauling arrangements are educated and moderated a period. Key Words: Visible Light, Physical layer security, Multi User, Spread-spectrum, security performance.","PeriodicalId":13661,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141920222","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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