International Journal of Advanced Research in Science, Communication and Technology最新文献

{"title":"Medicinal Plant Classification and it's Identification","authors":"Prof. Shailesh Kuzrdkar, Hrishikesh Dahule, Himanshi Waurkar, Rushita Likhar","doi":"10.48175/ijarsct-18264","DOIUrl":"https://doi.org/10.48175/ijarsct-18264","url":null,"abstract":"Indian Ayurvedic Medicine reached international level The basis of Ayurveda is herbal medicine. The pharmaceutical industry is starting to pay more. Be careful with herbs because their side effects and consequences are less than modern medicine and at the same time they are very expensive. The company efficiently and reliably uses leaf images from many deep and machine learning algorithms developed in recent years. In this study, leaves of 45 different medicinal plants were used and the deep learning method was used. A number of classification and identification methods were used using computer vision technology to achieve the best results. There are many medicinal plants according to the classification of the paper plant","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"45 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140973022","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}

{"title":"Concrete Breaking Strength Prediction Using Machine Learning","authors":"Dr. R. Premsudha, Dr. S. Kapilan, G. Viswanathan, M. Naganathan, S. Dhamodaran","doi":"10.48175/ijarsct-18237","DOIUrl":"https://doi.org/10.48175/ijarsct-18237","url":null,"abstract":"When it comes to estimating, classifying, and forecasting material strength based on changing material parameters, machine learning (ML) techniques have shown to be dependable methodologies. It is found that choosing the right machine learning technique depends on the characteristics of the problem and the available data. Therefore, fifteen different machine learning techniques were used to a specific dataset of concrete compressive strength in order to assess the accuracy of ML models to predict concrete compressive strength. Due to its excellent performance while dealing with continuous target variables and nonlinear interactions among the features and the target, the Support Vector Regressor (SVR) had the greatest prediction accuracy (88.18%) of all the ML methods employed. To guarantee the structural integrity of building projects, it is essential to predict the breaking strength of concrete. The goal of this project is to create a machine learning model that can forecast concrete's breaking strength depending on the mix's composition and curing circumstances. A dataset was created that included details regarding concrete samples, such as mix ratios, curing temperatures, curing times, and breaking strengths. recise estimation of concrete's compressive strength is crucial for the advancement and construction. A bibliometric analysis of the pertinent literature published in was conducted in order to comprehend the state of research in the field of concrete compressive strength prediction. The previous ten years have seen the first research in this sector. The database consisted of 31,35 journal articles published between 2012 and 2021 in the Web of Science core database. The knowledge map was created using Cite Space 6.1R2, a visualisation tool, to analyse the field at a macro level in terms of hotspot distribution, spatial and temporal distribution, and evolutionary trends, respectively. Next, we become specific and separate the prediction techniques for concrete compressive strength into two groups","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"36 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979783","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}

{"title":"Helmet and Number Plate Detection using YOLOV5","authors":"Dr. Manisha Pise, Ananya Saini, Payal Pochampalliwar, Neha Satpute, Pranjali Awale","doi":"10.48175/ijarsct-18239","DOIUrl":"https://doi.org/10.48175/ijarsct-18239","url":null,"abstract":"Ensuring the safety of motorcycle riders on roads is paramount, and the use of helmets plays a critical role in achieving this goal. Additionally, enforcing traffic laws, such as identifying motorcycles without helmets and recognizing their license plates, contributes significantly to maintaining road safety and upholding regulations. This project introduces a robust system designed specifically for detecting helmets and recognizing number plates on motorcycles. The system employs the YOLOv5 object detection model to identify motorcycles in images or videos, followed by assessing whether riders are wearing helmets. In cases where a rider is detected without a helmet, the system utilizes optical character recognition (OCR) to recognize the motorcycle's license plate. EasyOCR, a Python-based OCR library, is leveraged for extracting text from license plate images, and the extracted information is stored in a CSV file for subsequent analysis. This proposed system offers a comprehensive solution to improve road safety and enforce traffic regulations pertaining to helmet usage and license plate recognition for motorcycles","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"25 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979759","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}

{"title":"Automated Toilet Cleaner with Minimal Cleaning Resources","authors":"Sheik Mohamed Anas, Kathirvel, Naveenkumar, Kaviyarasan","doi":"10.48175/ijarsct-18238","DOIUrl":"https://doi.org/10.48175/ijarsct-18238","url":null,"abstract":"Technologies are increasing day, and at the same time our major task is cleanliness. From this paper we spread the message of hygiene and cleanliness of our surrounding. We need to maintain the hygiene or cleanliness in publics place or toilets. In cities government provides many facilities to make our surrounding clean. This paper is helpful to keep the India clean called as “Swachh Bharat”. In this system, we are targeting only on, how to maintain the hygiene in washrooms, and observing to the workers activities and also stopping the public to use the dirty washrooms. This paper are alerting to public about hygiene, and to keeping the surrounding clean. In our nation, sanitation has always been a major issue. Most significantly, this issue is not just concentrated to the rural areas but is also wide spread in urban and semi urban areas. People do not show the same level of concern when it comes to keeping the public sanitation systems clean as they show towards the ones at their homes. Right to good health and sanitation is one of the goals to be achieved as per the Millennium Development Goals of the United Nations Organisation, 2000.\u0000However in India, the scenario of public toilets is still dismal. One of the reasons for this is that the people do not bother to clean up after they use the toilet. These places are thus the breeding grounds of bacterial germs like Escherichia coli and many deadly diseases. Many people sometime prefer discomfort to using these toilets.\u0000Looking at such troubles, the decision to construct a self cleaning toilet was made that simply utilizes the weight of the person using it as its working mechanism. The system consists of a platform supported on springs and the lever arrangement that flushes after use. The lever is pivoted in such a way that it will lower itself when weight is applied downward and when the load is released, this will strike the flush and hence in this way water is flushed out to clean the toilet. So, our main intension of this paper is safe, hygiene and disease free washrooms.","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"22 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980383","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}

{"title":"Robust Adaptive Controller Design for Uncertain Second-Order Jerk Chaotic Systems","authors":"Yeong-Jeu Sun, Ting-Chia Chang, Sheng-Chieh Chen, Wei-Chun Liao, Sheng-Wei Huang, Yu-Chi Ho","doi":"10.48175/ijarsct-18255","DOIUrl":"https://doi.org/10.48175/ijarsct-18255","url":null,"abstract":"In this paper, the stabilization problem for a class of uncertain second-order jerk chaotic control systems is investigated. Combining differential and integral inequalities with nonlinear theory, we intend to construct a robust adaptive controller to promote a class of uncertain second-order jerk chaotic control systems to achieve the goal of adaptive stability. Finally, an example will be provided to illustrate the design process of the adaptive controller, and some numerical simulation results will be offered to demonstrate the correctness and effectiveness of the main result","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"51 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980928","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}

{"title":"Pandemic-onium Manager: An Information and Management Hub for Pandemics","authors":"Prof. Divyamani M K, Bhumika Raj, Muhsin Bashir, Ranganath V, Subhashish Das","doi":"10.48175/ijarsct-18245","DOIUrl":"https://doi.org/10.48175/ijarsct-18245","url":null,"abstract":"In the tumultuous wake of global pandemics, the efficient orchestration of resources, dissemination of information, and access to emergency services stand as imperative pillars of societal resilience. Enter the ”Pandemic-onium Manager” project, a beacon of hope amid chaos, aiming to revolutionize pandemic management through a holistic web application. This innovative platform empowers users with reliable information, seamless access to emergency services, versatile note-taking capabilities, meticulous inventory management, and personalized notifications tailored to pandemic-related events. Emboldened by a robust technological arsenal encompassing ReactJS for the frontend,ASP.NET WebAPI for the backend, MySQL for the database, and AWS for deployment, the Pandemic-onium Man- ager heralds a new era of scalability, security, and efficiency in data management. This paper embarks on a journey through the project’s objectives, technological prowess, key features, compliance measures, testing intricacies, documentation endeavors, and community engagement endeavors","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"19 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980122","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}

{"title":"AI Driven IoT(AIIoT) for Smart Agriculture","authors":"Arati Amol Kale, Swati Arvind Ghadge, Shefali Ajay Gaddam","doi":"10.48175/ijarsct-18248","DOIUrl":"https://doi.org/10.48175/ijarsct-18248","url":null,"abstract":"The agricultural industry is witnessing a significant shift due to the emergence of Artificial Intelligence driven Internet of Things (AIIoT), which is providing farmers with unparalleled automation capabilities and insights. The goal of this paper is to present a thorough review of AIIoT in smart agriculture, emphasising its uses, advantages, and consequences for decision-making. Smart agriculture decision-making is a game-changing technology that gives farmers the ability to maximise their operations and make well-informed judgements. Through the utilisation of advanced analytics, real-time data, and decision support systems, farmers may optimise crop yields, minimise expenses, and minimise risks. The agricultural industry will become more sustainable and productive as a result of farmers' increased ability to make decisions as the field of smart agriculture develops. The application of AI and IoT in smart agriculture is a game-changing technology that might completely alter how we grow and prepare food. Farmers can increase crop yields and quality, streamline operations, and contribute to a more effective and sustainable food supply chain by utilising AI and IoT. The advantages of AIIoT in smart agriculture are evident, despite the fact that there are still certain obstacles to be addressed, and its use is anticipated to increase in the years to come.","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"36 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140979735","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}

{"title":"Fake News Detection using Machine Learning","authors":"Sneha Sanghpriy Moon, Akshata Lonare, Aditi Chandekar, Mayuri Khandre, Prof. Mahesh Dumbere","doi":"10.48175/ijarsct-18244","DOIUrl":"https://doi.org/10.48175/ijarsct-18244","url":null,"abstract":"Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication. The question is how to authenticate the news and articles which are circulated among social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs & social networking sites. It is harmful for the society to believe on the rumors and pretend to be a news. The need of an hour is to stop the rumors especially in the developing countries like India, and focus on the correct, authenticated news articles. This paper demonstrates a model and the methodology for fake news detection. With the help of Machine learning and natural language processing, it is tried to aggregate the news and later determine whether the news is real or fake using Support Vector Machine. The results of the proposed model is compared with existing models. The proposed model is working well and defining the correctness of results upto 93.6% of accuracy","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"83 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140978633","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}

{"title":"A Review on “The In-vitro Study of Anticoagulant Activity of Different Plant Extract”","authors":"Mohini Pandurang Chaudhari, Payal Rajendra Wavhal, Madhuri Neharkar, Rumana Chaugule, Nutan Bhagwat Yewale, Prof. Mr. Sagar E. Tambe","doi":"10.48175/ijarsct-18236","DOIUrl":"https://doi.org/10.48175/ijarsct-18236","url":null,"abstract":"The aim of this review is to evaluate the plant extract which show highest anticoagulant activity. There are different plant extract to show the anticoagulant activity. On the basis of this study to know about which plant show maximum anticoagulant activity and which plant has minimum anticoagulant activity. The plants used are naturally obtained. They have other pharmacological properties but some plant have significant anticoagulant activity. The plant used for studied are Myrciaria plinioides, Terminalia bellerica, Gymnema sylvestre, Jatropa gossypiifolia, Allium sativum , Curcuma longa,Rubus ulmifolius, Gymnema sylvestre. Among these plant the Gymnema sylvestre has maximum anticoagulant activity, and the other plant show a significant anticoagulant activity. The prothrombin test, activated prothrombin test , thrombin test, recalcification method were used for the in vitro test of anticoagulant activity. The extract of plant were obtained by various extraction process such as maceration, soxhlet extraction, decoction method etc.","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"110 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140977974","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}

{"title":"Disease Prevalence Estimation","authors":"Lokesh Singhvi, Satyam Pathak, Harvi Patel, Bhoumik Rajput, Prof. Revati Raspayle","doi":"10.48175/ijarsct-18249","DOIUrl":"https://doi.org/10.48175/ijarsct-18249","url":null,"abstract":"Nowadays, disease prevalence estimation is a significant concern, with heart disease being one of the most common ailments. Unfortunately, the treatment of such diseases can be costly, often beyond the means of the average individual. However, we can mitigate this issue to some extent by accurately estimating disease prevalence before it reaches dangerous levels, using techniques such as Machine Learning and Data Mining.\u0000In the healthcare biomedical field, there's a vast amount of health data available, ranging from text to images. However, much of this data remains unexplored and unmined. Introducing a Disease Prevalence Estimation System could address this gap. Such a system would not only help in reducing costs but also enhance the quality of treatment for patients.\u0000Machine Learning and Data Mining techniques can be employed to construct this Disease Prevalence Estimation System. By analyzing patient profiles including factors like blood pressure, age, sex, cholesterol, and blood sugar levels, the system can predict the likelihood of individuals developing various health issues.\u0000Furthermore, the system can identify complex problems and make intelligent medical decisions, thereby improving overall healthcare outcomes. Performance evaluation can be done using metrics such as the confusion matrix, allowing for the calculation of accuracy, precision, and recall.\u0000In conclusion, a Disease Prevalence Estimation System has the potential to offer high performance and better accuracy, thus significantly contributing to the early detection and management of various diseases","PeriodicalId":510160,"journal":{"name":"International Journal of Advanced Research in Science, Communication and Technology","volume":"24 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980504","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}