Pub Date : 2024-05-02DOI: 10.59256/ijire.20240503001
Vyshnav Unnikrishnan, Jobin Mathew Samkutty, Navin M Mathew, Muhammad Shareef C S, Chandu Asok
The proliferation of Internet of Things (IoT) devices has introduced unprecedented connectivity and convenience but also heightened the vulnerability to botnet attacks. There are an increasing number of Internet of Things (IoT) devices connected to the network these days, and due to the advancement in technology, the security threads and cyberattacks, such as botnets, are emerging and evolving rapidly with high-risk attacks. These attacks disrupt IoT transition by disrupting networks and services for IoT devices. Many recent studies have proposed ML and DL techniques for detecting and classifying botnet attacks in the IoT environment. This project presents a straightforward approach to detect botnet activity within IoT networks through the utilization of machine learning techniques. By analyzing network traffic patterns and employing unsupervised learning algorithms, we demonstrate an effective method to identify and mitigate botnet threats in IoT environments. By this project we intend to offer a valuable contribution in enhancing the security of IoT ecosystem. Key Word: Internet of Things(IoT),cybersecurity, botnet attacks, machine learning(ML),UNSW-NB15 dataset, exploratory data analysis, XgBoost
物联网（IoT）设备的激增带来了前所未有的连接性和便利性，但同时也增加了僵尸网络攻击的脆弱性。如今，连接到网络上的物联网（IoT）设备越来越多，由于技术的进步，僵尸网络等安全问题和网络攻击也在迅速出现和发展，并伴有高风险攻击。这些攻击通过扰乱物联网设备的网络和服务来破坏物联网的过渡。最近的许多研究都提出了用于检测和分类物联网环境中僵尸网络攻击的 ML 和 DL 技术。本项目提出了一种利用机器学习技术检测物联网网络中僵尸网络活动的直接方法。通过分析网络流量模式和采用无监督学习算法，我们展示了在物联网环境中识别和减轻僵尸网络威胁的有效方法。通过这个项目，我们打算为提高物联网生态系统的安全性做出宝贵贡献。关键字物联网（IoT）、网络安全、僵尸网络攻击、机器学习（ML）、UNSW-NB15 数据集、探索性数据分析、XgBoost
{"title":"Detection of Botnet in IOT Using Machine Learning","authors":"Vyshnav Unnikrishnan, Jobin Mathew Samkutty, Navin M Mathew, Muhammad Shareef C S, Chandu Asok","doi":"10.59256/ijire.20240503001","DOIUrl":"https://doi.org/10.59256/ijire.20240503001","url":null,"abstract":"The proliferation of Internet of Things (IoT) devices has introduced unprecedented connectivity and convenience but also heightened the vulnerability to botnet attacks. There are an increasing number of Internet of Things (IoT) devices connected to the network these days, and due to the advancement in technology, the security threads and cyberattacks, such as botnets, are emerging and evolving rapidly with high-risk attacks. These attacks disrupt IoT transition by disrupting networks and services for IoT devices. Many recent studies have proposed ML and DL techniques for detecting and classifying botnet attacks in the IoT environment. This project presents a straightforward approach to detect botnet activity within IoT networks through the utilization of machine learning techniques. By analyzing network traffic patterns and employing unsupervised learning algorithms, we demonstrate an effective method to identify and mitigate botnet threats in IoT environments. By this project we intend to offer a valuable contribution in enhancing the security of IoT ecosystem. Key Word: Internet of Things(IoT),cybersecurity, botnet attacks, machine learning(ML),UNSW-NB15 dataset, exploratory data analysis, XgBoost","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"72 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141018021","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 : 2024-05-02DOI: 10.59256/ijire.20240503002
Bibin M Jacob, Devika Mohan, Shefina Shereef, Vaishnavi Nair S V, Stefin Thomas Pallathu
The security and effective management of health records is a key issue for today's digitized healthcare environment. In terms of data security, integrity and accessibility, traditional centralized systems face challenges. We propose a novel system of medical report management and dissemination using the Block-chain technology, as well as SHA1 encryption for addressing these issues. In order to store hashed medical reports, our system uses a decentralized block-chain network to ensure tamper-proof and immutable records. SHA1 is used to hash every medical report, generating a unique identifier that's stored on the Block-chain. The integration of Flask, Python's lightweight web framework, facilitates the creation of an easy user interface to interact with a system easily. Secure storage, effective distribution and granular control of medical reports are among the key features of our system. In order to maintain the integrity and confidentiality of data, patients, physicians or authorized persons should be able to use secure means for accessing and updating their healthcare records. The use of SHA1 increases system security by providing a reliable cryptographic hash. Our system is aimed at simplifying the management and distribution of medical reports, thereby improving efficiency and patient outcomes in addition to enhanced data protection and integrity. By ensuring security, transparency and decentralized solutions, we are confident that the proposal for a medical records management system has the potential to revolutionize this area.
{"title":"Medical Report Management and Distribution System on Blockchain","authors":"Bibin M Jacob, Devika Mohan, Shefina Shereef, Vaishnavi Nair S V, Stefin Thomas Pallathu","doi":"10.59256/ijire.20240503002","DOIUrl":"https://doi.org/10.59256/ijire.20240503002","url":null,"abstract":"The security and effective management of health records is a key issue for today's digitized healthcare environment. In terms of data security, integrity and accessibility, traditional centralized systems face challenges. We propose a novel system of medical report management and dissemination using the Block-chain technology, as well as SHA1 encryption for addressing these issues. In order to store hashed medical reports, our system uses a decentralized block-chain network to ensure tamper-proof and immutable records. SHA1 is used to hash every medical report, generating a unique identifier that's stored on the Block-chain. The integration of Flask, Python's lightweight web framework, facilitates the creation of an easy user interface to interact with a system easily. Secure storage, effective distribution and granular control of medical reports are among the key features of our system. In order to maintain the integrity and confidentiality of data, patients, physicians or authorized persons should be able to use secure means for accessing and updating their healthcare records. The use of SHA1 increases system security by providing a reliable cryptographic hash. Our system is aimed at simplifying the management and distribution of medical reports, thereby improving efficiency and patient outcomes in addition to enhanced data protection and integrity. By ensuring security, transparency and decentralized solutions, we are confident that the proposal for a medical records management system has the potential to revolutionize this area.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"2 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141018988","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 : 2024-05-02DOI: 10.59256/ijire.20240503003
Malathi T, Muhammed Nayif M Navab Metha, Nourin S, Prince Sajuvin, Jaison Mathew John
Most of individuals on earth make their living for the most part from horticultural work. Assuming there are any issues in that essential area, the populace's way of life will endure. Accordingly, it's vital for keep the agribusiness area in the right equilibrium by protecting something very similar from destructive impacts like plant sicknesses, dryness, and so on. In the rural area, ranchers get more cash-flow from cultivation than from different yields. These plants are helpless against numerous sicknesses rapidly, and early manual illness determination in crops is extremely difficult. stage. AI methods are utilized instead of manual illness distinguishing proof, which could prompt blunders. Picture.The impacted region of the picture is caught to finish the handling. Keyword: Image Processing, Resnet, Convolution Neural Network (CNN), Random Forest, Plant Diseases.
{"title":"Plant Disease Detection Using Machine Learning & Image Processing","authors":"Malathi T, Muhammed Nayif M Navab Metha, Nourin S, Prince Sajuvin, Jaison Mathew John","doi":"10.59256/ijire.20240503003","DOIUrl":"https://doi.org/10.59256/ijire.20240503003","url":null,"abstract":"Most of individuals on earth make their living for the most part from horticultural work. Assuming there are any issues in that essential area, the populace's way of life will endure. Accordingly, it's vital for keep the agribusiness area in the right equilibrium by protecting something very similar from destructive impacts like plant sicknesses, dryness, and so on. In the rural area, ranchers get more cash-flow from cultivation than from different yields. These plants are helpless against numerous sicknesses rapidly, and early manual illness determination in crops is extremely difficult. stage. AI methods are utilized instead of manual illness distinguishing proof, which could prompt blunders. Picture.The impacted region of the picture is caught to finish the handling. Keyword: Image Processing, Resnet, Convolution Neural Network (CNN), Random Forest, Plant Diseases.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"38 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141021617","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 : 2024-05-01DOI: 10.59256/ijire.20240502042
Maheswari J, Sowmiya B, Sowmiya K, Thirisha S, Vishnupriya G
The project titled "Revolutionizing Blind Navigation through AI Voices" presents a novel approach to aid visually impaired individuals in navigating their surroundings independently and safely. By harnessing the power of artificial intelligence (AI) and voice technology, our system provides real-time guidance and assistance to users. Through the integration of advanced object detection algorithms, such as YOLO (You Only Look Once), our solution enables accurate detection and recognition of various objects in the environment. The detected objects are then translated into audio instructions, delivered through AI-generated voices, to help users understand their surroundings and navigate effectively. Moreover, the system is seamlessly integrated with a web interface using Flask, allowing for remote control and interaction. Our project contributes to the advancement of assistive technologies for the visually impaired, offering a user-friendly and reliable solution for enhanced mobility and independence.
{"title":"Revolutionizing Blind Navigation through AI Voices","authors":"Maheswari J, Sowmiya B, Sowmiya K, Thirisha S, Vishnupriya G","doi":"10.59256/ijire.20240502042","DOIUrl":"https://doi.org/10.59256/ijire.20240502042","url":null,"abstract":"The project titled \"Revolutionizing Blind Navigation through AI Voices\" presents a novel approach to aid visually impaired individuals in navigating their surroundings independently and safely. By harnessing the power of artificial intelligence (AI) and voice technology, our system provides real-time guidance and assistance to users. Through the integration of advanced object detection algorithms, such as YOLO (You Only Look Once), our solution enables accurate detection and recognition of various objects in the environment. The detected objects are then translated into audio instructions, delivered through AI-generated voices, to help users understand their surroundings and navigate effectively. Moreover, the system is seamlessly integrated with a web interface using Flask, allowing for remote control and interaction. Our project contributes to the advancement of assistive technologies for the visually impaired, offering a user-friendly and reliable solution for enhanced mobility and independence.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"61 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141035427","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}
High rise building is the most frequently used word in all most all construction activities especially in rapidly growing cities in terms of development and population. National Building Code (NBC) defines a high-rise as “All buildings 15 m or above in height (a building more than 4 storeys). The employment opportunities and facilities offered by the developing cities makes people to migrate towards urban areas which create the land scarcity for both Industrial and residential occupants. To satisfy the needs considering the future demand of habitable area and efficient use of land without expanding the boundaries of the cities makes people to choose high rise building it also facilitates with stunning views less noise pollution etc. STAAD is a popular structural analysis application known for analysis, diverse applications of use, Interoperability, and time-saving capabilities. STAAD helps structural engineers perform 3D structural Analysis and design for both steel and concrete structures. It ensures on-time and cost-effective Completion of steel, concrete, timber, aluminium, and cold-formed steel structures and designs, Regard less of complexity. We conclude that in this study we consider plot area 70 m x 24 m of g+12 Building consisting of 72 flats located kesarapalli near vijayawada Located in zone 3. we are going to analyse the high rise building for shear force and bending moments and design of critical sections of slab staircase footing by considering various loads such as with and without wind load, imposed load, dead loads. Key Word: High rise building, wind load, STAAD pro.
高层建筑是所有建筑活动中最常用的词汇，尤其是在发展和人口迅速增长的城市。国家建筑规范》（NBC）将高层建筑定义为 "所有高度在 15 米或以上的建筑（4 层以上的建筑）"。发展中城市提供的就业机会和设施使人们向城市地区迁移，这就造成了工业用地和住宅用地的稀缺。为了在不扩大城市边界的情况下满足未来对可居住面积的需求和有效利用土地，人们选择了高层建筑。STAAD 是一款广受欢迎的结构分析应用程序，以分析、多样化应用、互操作性和省时等功能而著称。STAAD 可帮助结构工程师对钢结构和混凝土结构进行三维结构分析和设计。它可以确保钢结构、混凝土结构、木结构、铝结构和冷弯型钢结构和设计的按时、经济高效地完成，而无需考虑复杂性。我们的结论是，在这项研究中，我们考虑到地块面积为 70 m x 24 m 的 g+12 建筑由 72 个单位组成，位于维贾亚瓦达附近的 kesarapalli，地处 3 区。我们将分析高层建筑的剪力和弯矩，并通过考虑各种荷载（如有风荷载和无风荷载、外加荷载、自重荷载）来设计楼板楼梯地脚的关键部分。关键词：高层建筑、风荷载、STAAD pro。
{"title":"Analysis and Design of High-Rise (G +12) Building Using STAAD Pro","authors":"Dr. Pusala Kodanda Rama Rao, Koppula Siva Rama Krishna Reddy, Polagani Tej Sai, Mathangi Bharat Kumar, Murari Naveen Kumar, Pamarthi Varun","doi":"10.59256/ijire.20240502034","DOIUrl":"https://doi.org/10.59256/ijire.20240502034","url":null,"abstract":"High rise building is the most frequently used word in all most all construction activities especially in rapidly growing cities in terms of development and population. National Building Code (NBC) defines a high-rise as “All buildings 15 m or above in height (a building more than 4 storeys). The employment opportunities and facilities offered by the developing cities makes people to migrate towards urban areas which create the land scarcity for both Industrial and residential occupants. To satisfy the needs considering the future demand of habitable area and efficient use of land without expanding the boundaries of the cities makes people to choose high rise building it also facilitates with stunning views less noise pollution etc. STAAD is a popular structural analysis application known for analysis, diverse applications of use, Interoperability, and time-saving capabilities. STAAD helps structural engineers perform 3D structural Analysis and design for both steel and concrete structures. It ensures on-time and cost-effective Completion of steel, concrete, timber, aluminium, and cold-formed steel structures and designs, Regard less of complexity. We conclude that in this study we consider plot area 70 m x 24 m of g+12 Building consisting of 72 flats located kesarapalli near vijayawada Located in zone 3. we are going to analyse the high rise building for shear force and bending moments and design of critical sections of slab staircase footing by considering various loads such as with and without wind load, imposed load, dead loads. Key Word: High rise building, wind load, STAAD pro.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"3 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140653428","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 paper introduces AspireAI, an AI chatbot designed for comprehensive career guidance. With the proliferation of Artificial Intelligence (AI), integrating such technology into career counseling is increasingly vital. Leveraging Large Language Models (LLMs), AspireAI provides personalized career information, job search advice, and educational recommendations. Our methods entail training LLMs on vast datasets of career-related content to enhance conversational capabilities. Results demonstrate AspireAI's efficacy in delivering tailored guidance, aiding users in making informed career decisions. Through this research, we highlight the importance and potential of AI-driven solutions in facilitating career exploration and advancement. Keyword: AI Chatbot, Career Guidance, Large Language Models (LLMs), Personalized Guidance, Job Search Advice, Educational Recommendations
{"title":"ASPIREAI: AI Chatbot for Career Guidance","authors":"Abhishek Yogesh Dhamdhere, Neha Raju Bhosale, Aditi Chandrakant Joshi, Vaidehi Vishwanath Kale, Aniket Avinash Chavan, M.S. Pokale","doi":"10.59256/ijire.20240502033","DOIUrl":"https://doi.org/10.59256/ijire.20240502033","url":null,"abstract":"This paper introduces AspireAI, an AI chatbot designed for comprehensive career guidance. With the proliferation of Artificial Intelligence (AI), integrating such technology into career counseling is increasingly vital. Leveraging Large Language Models (LLMs), AspireAI provides personalized career information, job search advice, and educational recommendations. Our methods entail training LLMs on vast datasets of career-related content to enhance conversational capabilities. Results demonstrate AspireAI's efficacy in delivering tailored guidance, aiding users in making informed career decisions. Through this research, we highlight the importance and potential of AI-driven solutions in facilitating career exploration and advancement. Keyword: AI Chatbot, Career Guidance, Large Language Models (LLMs), Personalized Guidance, Job Search Advice, Educational Recommendations","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"60 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140655676","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 : 2024-04-24DOI: 10.59256/ijire.20240502032
R. R, Sanmathi K R, R. S R
Water footprint assessment has become a useful method for assessing how much water is used by products and activities related to humans, offering insights into how water resources might be managed sustainably. While agricultural production accounts for the majority of water consumption worldwide, the industrial and residential sectors also use large amounts of water and cause pollution. This review article provides an examination of the approaches and uses of water footprint assessment in a range of industries and geographical areas. The notion of water footprint and its elements green, blue, and grey water footprints as well as the corresponding computation techniques are introduced at the outset of the work. The most recent developments in spatially explicit modelling and life cycle assessment techniques, it examines the development of water footprint assessment procedures. The paper explores the many uses of water footprint assessment, from consumer items and urban water management to industrial operations and agricultural output. It provides case studies and real-world examples that show how water footprint analysis may be applied practically to address issues with pollution, water shortages, and sustainability in various settings. The study also looks at the difficulties and constraints that come with assessing the water footprint, such as methodological uncertainty, data availability, and temporal and geographical variability. It talks about current studies as well as potential paths forward for improving the reliability and usability of water footprint measurement instruments. As a comprehensive and integrated method for measuring and controlling the effects of human-induced water usage on regional and global water resources, this study concludes by highlighting the importance of water footprint assessment. In order to promote sustainable water management practices, it highlights the necessity of multidisciplinary collaboration and stakeholder involvement. Keyword: Water Footprint, Sustainability, Life Cycle Assessment, Spatial Analysis.
{"title":"Water Footprint: A Review Based on Concepts, Methods, and Implications","authors":"R. R, Sanmathi K R, R. S R","doi":"10.59256/ijire.20240502032","DOIUrl":"https://doi.org/10.59256/ijire.20240502032","url":null,"abstract":"Water footprint assessment has become a useful method for assessing how much water is used by products and activities related to humans, offering insights into how water resources might be managed sustainably. While agricultural production accounts for the majority of water consumption worldwide, the industrial and residential sectors also use large amounts of water and cause pollution. This review article provides an examination of the approaches and uses of water footprint assessment in a range of industries and geographical areas. The notion of water footprint and its elements green, blue, and grey water footprints as well as the corresponding computation techniques are introduced at the outset of the work. The most recent developments in spatially explicit modelling and life cycle assessment techniques, it examines the development of water footprint assessment procedures. The paper explores the many uses of water footprint assessment, from consumer items and urban water management to industrial operations and agricultural output. It provides case studies and real-world examples that show how water footprint analysis may be applied practically to address issues with pollution, water shortages, and sustainability in various settings. The study also looks at the difficulties and constraints that come with assessing the water footprint, such as methodological uncertainty, data availability, and temporal and geographical variability. It talks about current studies as well as potential paths forward for improving the reliability and usability of water footprint measurement instruments. As a comprehensive and integrated method for measuring and controlling the effects of human-induced water usage on regional and global water resources, this study concludes by highlighting the importance of water footprint assessment. In order to promote sustainable water management practices, it highlights the necessity of multidisciplinary collaboration and stakeholder involvement. Keyword: Water Footprint, Sustainability, Life Cycle Assessment, Spatial Analysis.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"40 27","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140663063","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 : 2024-04-18DOI: 10.59256/ijire.20240502031
Sandeep Kumar Verma, Vipin Kumar
There is a major problem in India for generation of biomedical waste from health care units, research laboratories, clinics and other medical sources. Generation of waste adversely affect the whole environment for human being. Therefore Utilization of medical waste ash is a challenging work for all over India. Some researches revealed the scope for the use of medical waste ash in concrete as partly replacing of cement. In this paper the study describes the workability, density and compressive strength of concrete after partly replacing of cement with medical waste ash. Keyword: Medical waste, ash, concrete, coarse, aggregate, workability.
{"title":"Investigation on Utilization of Medical Waste Ash in Concrete","authors":"Sandeep Kumar Verma, Vipin Kumar","doi":"10.59256/ijire.20240502031","DOIUrl":"https://doi.org/10.59256/ijire.20240502031","url":null,"abstract":"There is a major problem in India for generation of biomedical waste from health care units, research laboratories, clinics and other medical sources. Generation of waste adversely affect the whole environment for human being. Therefore Utilization of medical waste ash is a challenging work for all over India. Some researches revealed the scope for the use of medical waste ash in concrete as partly replacing of cement. In this paper the study describes the workability, density and compressive strength of concrete after partly replacing of cement with medical waste ash. Keyword: Medical waste, ash, concrete, coarse, aggregate, workability.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":" 35","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140687418","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 : 2024-04-16DOI: 10.59256/ijire.20240502030
P. Gayatri, T. Ashish, B. Sankar, P. Evan Theodar, P. Srinivas Rao
Cryptocurrency has emerged as a transformative force in the financial realm, garnering widespread attention and acceptance. However, its dynamic nature and inherent uncertainties pose significant challenges for investors. This study delves into the factors shaping cryptocurrency value formation by harnessing the power of advanced artificial intelligence frameworks. Specifically, we employ fully connected Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) Recurrent Neural Network to analyze the price dynamics of prominent cryptocurrencies such as Bitcoin, Ethereum, and Ripple. Our research reveals that ANN tends to rely more heavily on long-term historical data, whereas LSTM exhibits a penchant for short-term dynamics. Interestingly, LSTM demonstrates superior efficiency in leveraging historical information, yet with adequate data, ANN can achieve comparable accuracy. Our findings shed light on the predictability of cryptocurrency market prices, albeit the interpretation may vary depending on the machine-learning model utilized. This study underscores the significance of leveraging artificial intelligence in comprehending and forecasting cryptocurrency market trends, thereby mitigating investment risks in this dynamic landscape. Keyword: Cryptocurrency, Artificial Intelligence, Market Trends, Price Dynamics, Bitcoin.
{"title":"Exploring Cryptocurrency Market Trends Using Artificial Intelligence","authors":"P. Gayatri, T. Ashish, B. Sankar, P. Evan Theodar, P. Srinivas Rao","doi":"10.59256/ijire.20240502030","DOIUrl":"https://doi.org/10.59256/ijire.20240502030","url":null,"abstract":"Cryptocurrency has emerged as a transformative force in the financial realm, garnering widespread attention and acceptance. However, its dynamic nature and inherent uncertainties pose significant challenges for investors. This study delves into the factors shaping cryptocurrency value formation by harnessing the power of advanced artificial intelligence frameworks. Specifically, we employ fully connected Artificial Neural Network (ANN) and Long Short-Term Memory (LSTM) Recurrent Neural Network to analyze the price dynamics of prominent cryptocurrencies such as Bitcoin, Ethereum, and Ripple. Our research reveals that ANN tends to rely more heavily on long-term historical data, whereas LSTM exhibits a penchant for short-term dynamics. Interestingly, LSTM demonstrates superior efficiency in leveraging historical information, yet with adequate data, ANN can achieve comparable accuracy. Our findings shed light on the predictability of cryptocurrency market prices, albeit the interpretation may vary depending on the machine-learning model utilized. This study underscores the significance of leveraging artificial intelligence in comprehending and forecasting cryptocurrency market trends, thereby mitigating investment risks in this dynamic landscape. Keyword: Cryptocurrency, Artificial Intelligence, Market Trends, Price Dynamics, Bitcoin.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"23 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697445","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 : 2024-04-13DOI: 10.59256/ijire.20240502029
Krishna A, Magan Lodhi, Khushi Jain, Navya A
This paper provides a analysis of previous research on sign language recognition systems and their impact on Providing meaningful interaction among non-verbal individuals. It introduces a real-time sign language interpreter that translates text into gestures and vice-versa, accommodating regional sign languages and promoting personal expression. In a manner distinct from previous systems, it emphasizes individualization and includes text chat features for seamless communication. By enabling users to create and share their own gestures, it Promotes cultural diversity and authentic self-expression, promoting inclusivity and empowerment within the non-verbal community. This innovative solution also alleviates the pressure on non-verbal communication users to perform gestures in front of a camera for accurate recognition, addressing issues with outdated sign languages and the lack of personal sign gestures. Key Word: Sign Language Recognition, Text-to-sign Translation, Sign Language Interpreter, Sign Language Evolution, Recognition Models, Recognition Techniques.
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