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Well Being Assistance Chat Application 健康援助聊天应用程序
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s066
Gaurav Dhavala, Sunil K. Sheoran, Atharva Arya, Mrudul Vajpayee, Vipul Jain, Divyajyoti Shrivastava
{"title":"Well Being Assistance Chat Application","authors":"Gaurav Dhavala, Sunil K. Sheoran, Atharva Arya, Mrudul Vajpayee, Vipul Jain, Divyajyoti Shrivastava","doi":"10.47392/irjash.2023.s066","DOIUrl":"https://doi.org/10.47392/irjash.2023.s066","url":null,"abstract":"Nowadays chatbots are widely used by almost every ecommerce, commercial and public welfare website to provide an intellectually rapid solution to cus-tomers. It provides extensive range of solutions from customer service to sug-gesting sales options, providing better service and customer satisfaction. Ever since the introduction of first Chabot, technological developments in the field of Artificial Intelligence has lead to tremendous advancements in designing chatbots that can efficiently mimic human conversations. This paper presents implementation of a chatbot for providing wellbeing assistance to the users. Wellbeing assistance chatbot not only offers effortless assistance to frequent enquiries of the users but additionally indicates the gravity of medical situation to the user. It can converse with people about their health condition and prescribe medications for common sickness. It can be deployed in hospitals for efficiently reducing overcrowding of the patients. Accuracy of the working model can be further increased by creating and using real time demographic data to train the model even after deployment. The proposed wellbeing assistance Chabot is based on Natural language","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129384973","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}
引用次数: 1
Anthracnose Disease Detection in Cashew Leaf Using Machine Learning Technique Based on Contour Detection and Principal Component Analysis 基于轮廓检测和主成分分析的腰果叶炭疽病检测
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s070
S. P, K. P.
{"title":"Anthracnose Disease Detection in Cashew Leaf Using Machine Learning Technique Based on Contour Detection and Principal Component Analysis","authors":"S. P, K. P.","doi":"10.47392/irjash.2023.s070","DOIUrl":"https://doi.org/10.47392/irjash.2023.s070","url":null,"abstract":"Detecting and classifying leaf diseases in cashew crops is critical for farmers to find pest and disease infections. Cashew leaf diseases can reduce pro-ductivity if not detected early. Creating an automated method utilizing image processing for leaf disease identification decreases time and expense and pri-marily contributes to a rise in cashew nut yield. For image segmentation, canny edge detection and an active contour model are utilized. A feature extraction method, Principal Component Analysis (PCA), is applied when the contour has been applied. After the features have been extracted, they are submitted for categorization. This study analyzed several classifiers’ accuracy, precision, and recall values. These classifiers included Random Forest, SVM, KNN, and Naive Bayes. This research tries to answer whether a machine learning classifier provides the best results when the diseased area is divided using the canny edge detection and contour detection technique.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127106199","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}
引用次数: 0
Multilingual Image caption Generator using Big data and Deep Learning 使用大数据和深度学习的多语言图像标题生成器
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s047
Naresh Grover, Anchita Singh, Suganeshwari G
{"title":"Multilingual Image caption Generator using Big data and Deep Learning","authors":"Naresh Grover, Anchita Singh, Suganeshwari G","doi":"10.47392/irjash.2023.s047","DOIUrl":"https://doi.org/10.47392/irjash.2023.s047","url":null,"abstract":"Automatic image captioning aims to produce a descriptive sentence about a picture. For this task, we are creating a model that will spit out an English sentence when an image is given as input describing the image’s subject. Scien-tists in the field of cognitive computing have paid much attention to it in recent years. The endeavor is challenging because it requires merging ideas from two distinct but related disciplines: natural language processing and computer vision. Using the integration of CNN with LSTM, we developed a model for generating image captions. The ideas behind a Convolutional Neural Network and a Long Short-Term Memory model were combined to create this model. The convolutional neural network serves as the encoder, extracting information from images. At the same time, the long short-term memory is responsible for the decoder role, coming up with words to describe the image. The problem arises when the dataset is significant, and it takes weeks for systems to have only CPU support to train the network to decrease the time it is required to","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121511781","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}
引用次数: 1
Automatic License Plate Recognition System Using YOLOv4 基于YOLOv4的车牌自动识别系统
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s038
Amogh Mohta, A. Swaroop, Katkuri Fhanindra Reddy, Manjula R
{"title":"Automatic License Plate Recognition System Using YOLOv4","authors":"Amogh Mohta, A. Swaroop, Katkuri Fhanindra Reddy, Manjula R","doi":"10.47392/irjash.2023.s038","DOIUrl":"https://doi.org/10.47392/irjash.2023.s038","url":null,"abstract":"In this research paper, we’ll talk about ALPR technology, which has gained popularity recently because of all the many ways it may be used. The fundamental benefit of this technology is that it may be utilized for a variety of purposes, including travel time analysis, intelligent parking, automated toll collec-tion, intelligent transportation systems in smart cities, and traffic management. Automated License Plate Recognition (ALPR) reads the vehicle’s registration number by first using YOLOv4 for object recognition following which we use OpenCV to enlarge the license plate image and identify the character boxes after which we use Tesseract optical character recognition to identify the various characters and form the license plate number. This system uses several image processing methods to recognize automobiles swiftly and automatically in video or picture material. As technology develops quickly with the introduction of machine learning and deep learning, the cost of computing falls, and the accuracy of used image processing methods rises, the usage of ALPR systems is becoming more widespread. In today’s congested traffic system, a license plate detection system is crucial. It aids in monitoring compliance with traffic laws and other law enforcement operations. There are many instances of reckless driving in India when vehicles break several traffic laws. As a result, a license plate detection system has been suggested and put into use throughout the years to assist with quick and simple traffic law enforcement by automobiles. This work offers a powerful method for character localization, segmentation, and identification inside the located plate. We are going to utilize tesseract OCR and the YoLo V4 approach to solve the License plate recognition system issue and deliver our suggested system with high accuracy.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131174945","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}
引用次数: 1
Crop Classification using Semi supervised Learning on Data Fusion of SAR and Optical Sensor 基于半监督学习的SAR与光学传感器数据融合作物分类
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s060
A. R, Gopikrishnan C, Varun Raj A, V. M, Mr. Jayakrishnan
{"title":"Crop Classification using Semi supervised Learning on Data Fusion of SAR and Optical Sensor","authors":"A. R, Gopikrishnan C, Varun Raj A, V. M, Mr. Jayakrishnan","doi":"10.47392/irjash.2023.s060","DOIUrl":"https://doi.org/10.47392/irjash.2023.s060","url":null,"abstract":"Crop maps are essential tools for creating crop inventories, forecasting yields, and guiding the use of efficient farm management techniques. These maps must be created at highly exact scales, necessitating difficult, costly, and time-consuming fieldwork. Deep learning algorithms have now significantly enhanced outcomes when using data in the geographical and temporal dimensions, which are essential for agricultural research. The simultaneous availability of Sentinel-1 (synthetic aperture radar) and Sentinel-2 (optical) data provides an excellent chance to combine them. Sentinel 1 and Sentinel 2 data sets were collected for the Cape Town, South Africa, region. With the use of these datasets, we use the fusion technique, particularly the layer-level fusion strategy, one of the three fusion procedures (input level, layer level, and deci-sion level). Also, we will compare the results before and after the fusion and discuss the recommended method for converting from a multilayer perceptron decoder to a semi-supervised decoder architecture.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123907252","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}
引用次数: 0
Histobot: Question Generation System Using Deep Learning Techniques Histobot:使用深度学习技术的问题生成系统
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s071
Docca Pranav, Badri Prasad V R
{"title":"Histobot: Question Generation System Using Deep Learning Techniques","authors":"Docca Pranav, Badri Prasad V R","doi":"10.47392/irjash.2023.s071","DOIUrl":"https://doi.org/10.47392/irjash.2023.s071","url":null,"abstract":"From the analysis of recent researches of automatic question generation using deep learning techniques, we examined papers between 2022 and early 2023 from the examination of recent research on automatic question production using deep learning techniques. Our study comes after the survey report that broadens the analysis of earlier evaluations of AQG content that surfaced between late 2014 and early 2019. We examined the researched works that were included, looking at things like the (1) framework for question generation and (2) generating method. We discovered that contemporary methods fre-quently rely on generative frameworks that deploy Transformer-based models and GPT-n series, which are more efficient in terms of analysis and perfor-mances. We discovered that question creation has gained popularity recently and has significantly improved the educational field. Yet, it can be challenging to produce automatic questions and create the necessary question patterns, structures, and forms. Our additional research advises testing out more prac-tical, efficient models and strategies for autonomous question generating.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"708 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123961607","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}
引用次数: 0
Blockchain-Based Organ Donation Platform: Defeating Trafficking and Ensuring Transparency 基于区块链的器官捐赠平台:打击贩运并确保透明度
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s048
Prasoon Soni, Alok Mathur, Dhruv Patel, M. R
{"title":"Blockchain-Based Organ Donation Platform: Defeating Trafficking and Ensuring Transparency","authors":"Prasoon Soni, Alok Mathur, Dhruv Patel, M. R","doi":"10.47392/irjash.2023.s048","DOIUrl":"https://doi.org/10.47392/irjash.2023.s048","url":null,"abstract":"Organ donation and organ trafficking are significant global health issues that pose ethical and legal challenges. There is a significant shortage of available organs for transplantation compared to the demand, resulting in the emergence of an illegal market for organs. This black market exploits and takes advan-tage of vulnerable individuals, who are coerced into selling their organs for transplant purposes. To address these issues, this research proposes using blockchain technology as a tool for improving transparency and traceability in the organ donation and transplantation process. The platform is built on top of the Polygon blockchain, using smart contracts to automate various aspects of the process, such as verifying donor and recipient identities, managing organ matching, and releasing organ donation records. Patient information is securely stored using MongoDB, while decentralized digital identities ensure data security and privacy. An administrative dashboard provides a user-friendly interface for managing the system, and regular data analytics and monitoring track key metrics. The use of blockchain technology has the potential to improve the safety and ethical integrity of the organ transplantation","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130577087","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}
引用次数: 1
Comparative Study of CNN Models for Defect Detection in Food Packets 食品包装缺陷检测的CNN模型比较研究
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s055
Neeti Shukla, Asmita A. Moghe
{"title":"Comparative Study of CNN Models for Defect Detection in Food Packets","authors":"Neeti Shukla, Asmita A. Moghe","doi":"10.47392/irjash.2023.s055","DOIUrl":"https://doi.org/10.47392/irjash.2023.s055","url":null,"abstract":"Industry 4.0 is the term which promises a new industrial revolution. It is an amalgamation of advanced manufacturing techniques and Internet of Things(IoT) to produce such manufacturing systems which are interconnected, and can communicate, do analysis, and utilize the information to drive further intelligent action back in the physical world. Industrial Internet of Things (IIoT) involve application of IoT in manufacturing and other industrial processes to enhancing the working condition, and improvement of operational efficiency (Foukalas et al.). This paper reviews the recent work on industry 4.0 for automated defect detection in food packaging industry. This will help to reduce the complexity and improve the speed and accuracy of detection. This paper discusses the challenges and applications of industry 4.0 in general and further proposes a method to compare how various CNN models can be used for detecting the defects in food packaging industry. In this work seven (Alexnet, Resnet50, Resnet101, Densenet, VGG16, VGG19 and Squeezenet ) different convolution neural networks are subjected to detecting the defects","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133875543","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}
引用次数: 0
A Review of Emerging Information and Communication Technologies for Smart and Future Horticultural Supply Chain 面向智能和未来园艺供应链的新兴信息通信技术综述
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s014
Y. M., Jothi Basu R
{"title":"A Review of Emerging Information and Communication Technologies for Smart and Future Horticultural Supply Chain","authors":"Y. M., Jothi Basu R","doi":"10.47392/irjash.2023.s014","DOIUrl":"https://doi.org/10.47392/irjash.2023.s014","url":null,"abstract":"Fruits, and vegetables (FVs) are an important element of a human’s healthy diet since they include essential minerals and vitamins. The WHO recom-mends that 400 grams of FVs be ingested daily in the human diet to reduce the risk of chronic disorders. However, according to the UN, almost half of all FVs produced globally are thrown out each year. It is vital to use modern technology, particularly information and communication technology (ICT), to decrease food waste and ensure food safety from farm to fork. The aim of this study is to review the current status of trending ICT implementation in the horticultural supply chain (HSC) and propose recommendations to both researchers as well as practitioners. This study uses a systematic literature review (SLR) technique, and a novel framework is created for this purpose. Articles pub-lished in this area between January 1, 2011, and October 31, 2022, are considered for evaluation. After applying filtering criteria, the final eligible 39 articles were thoroughly reviewed and analyzed. The gap in the adoption of ICTs in HSC, and vegetables are less researched, and objective such as food security are not explored, which are key findings of this research work","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134433637","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}
引用次数: 0
Using a Hybrid Model of Machine LearningAlgorithms for Efficient Cardiovascular illness Prediction 基于机器学习算法的混合模型高效心血管疾病预测
International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s064
Hari Krishna T, Maimoon S, Naveena Jyothi J, RaviSankar Reddy R, Pavani C, Narendra Kumar Raju K
{"title":"Using a Hybrid Model of Machine LearningAlgorithms for Efficient Cardiovascular illness Prediction","authors":"Hari Krishna T, Maimoon S, Naveena Jyothi J, RaviSankar Reddy R, Pavani C, Narendra Kumar Raju K","doi":"10.47392/irjash.2023.s064","DOIUrl":"https://doi.org/10.47392/irjash.2023.s064","url":null,"abstract":"Researchers have paid more attention to the field of medicine. Researchers have found several kinds of factors which leads to human early mortality. According to the relevant studies, illnesses are brought on by a variety of factors and heart-related illnesses is one of them. Numerous scholars suggested unconventional ways to prolong human life and aid medical professionals in the diagnosis, treatment and management of cardiac disease. Some practical techniques help the expert make a choice, but every effective plan contains some drawbacks. The suggested techniques in this paper examines an act of Decision Tree, Random Forest, XGBoost and Hybrid Model. Based on the results, we created a hybrid approach to archive data with more precision.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133676242","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}
引用次数: 1
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