International Research Journal on Advanced Science Hub最新文献_第9页

Smart Traffic Vehicle monitoring and Signal Allocation using YOLO 基于YOLO的智能交通车辆监控与信号分配

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s028

R. P., Sandeep P, Suganyadevi S

{"title":"Smart Traffic Vehicle monitoring and Signal Allocation using YOLO","authors":"R. P., Sandeep P, Suganyadevi S","doi":"10.47392/irjash.2023.s028","DOIUrl":"https://doi.org/10.47392/irjash.2023.s028","url":null,"abstract":"The trafﬁc control system in India is now inﬂexible to the continuously increas-ing number of vehicles on the road. Fixed trafﬁc light timing systems are a poor method of controlling trafﬁc ﬂow. Trafﬁc lights are the fundamental component in trafﬁc ﬂow control through predetermined waiting and going times. A smart approach to adjust trafﬁc light timing based on the number of vehicles in each lane is part of an intelligent trafﬁc system. The average journey and waiting time for passengers will be reduced while the safety, dependability, and speed of the trafﬁc ﬂow is all increased. Designing an effective automated Trafﬁc Time Saving system is the goal. The system is used for trafﬁc management. In this proposed application ﬁrst takes a picture of the car. Images are ﬁrst converted from RGB to grayscale, then the vehicle picture is retrieved using image segmentation. After applying segmentation to the ready image, neural networks determine whether or not individual section contains a car. The successful parts will be counted by a counter. Lastly, a Graphical User Interface (GUI) will show the appropriate times for each light color.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"1 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":"129248758","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

Evaluation of Feature Engineering Techniques for Improving CVE Vulnerability Classification 改进CVE漏洞分类的特征工程技术评价

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s026

Mounesh Marali, D. R, Narendran Rajagopalan

{"title":"Evaluation of Feature Engineering Techniques for Improving CVE Vulnerability Classification","authors":"Mounesh Marali, D. R, Narendran Rajagopalan","doi":"10.47392/irjash.2023.s026","DOIUrl":"https://doi.org/10.47392/irjash.2023.s026","url":null,"abstract":"This paper presents a three-stage approach to analyzing Common Vulnerabilities and Exposures (CVE) vulnerability datasets using machine learning techniques. In the ﬁrst stage, K-Means clustering, and Linear discriminant analysis (LDA) topic modeling are applied to identify distinct clusters and topics within the dataset. The Elbow method is used to determine the optimal number of clusters for K-Means, while Grid Search is used to ﬁnd the best topic model for LDA. After labeling 100 random samples from each cluster, the data is split into training and testing sets for use in various classiﬁcation algorithms in the third stage. The paper contributes to the ﬁeld by proposing a novel approach to analyzing CVE vulnerability datasets that combines clustering and classiﬁcation techniques. The use of K-Means clustering and LDA topic modeling allows for the identiﬁcation of distinct clusters and topics within the dataset, which can be used to improve the accuracy of classiﬁcation algorithms. The study highlights the importance of using pre-trained word embeddings and dis-cusses the limitations of the proposed approach. Overall, the paper provides valuable insights into the analysis of CVE vulnerability datasets and","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"86 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114023539","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

Stroke prediction using 1DCNN with ANOVA 基于方差分析的1DCNN脑卒中预测

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s050

Mallikarjunamallu K, K. Syed

{"title":"Stroke prediction using 1DCNN with ANOVA","authors":"Mallikarjunamallu K, K. Syed","doi":"10.47392/irjash.2023.s050","DOIUrl":"https://doi.org/10.47392/irjash.2023.s050","url":null,"abstract":"Stroke and heart disease are among the most common outcomes of hypertension. Each year, heart disease, stroke, and other cardiovascular disorders claim the lives of more than 877,500 people in the United States, making them the ﬁrst and ﬁfth leading causes of death, so being able to predict them early helps save lives. A lot of research has been done to reach this goal. Machine learning models are mostly used for this purpose. For the ﬁrst time in this study, we have used the Deep Learning (DL) model, i.e., one dimensional convolutional neural network (1D CNN) . In this study, ﬁrst we extracted important features using the Analysis of variance (ANOVA) method. Then the data set with the new features that came up was given to the model. Then we compare all machine learning algorithms—K-Nearest Neighbors (KNN), Support Vec-tor Machine (SVM), Logistic Regression (LR), Random Forest Classiﬁer (RF), Gradient Boosting Clas-siﬁer (XGB), and LoLight gradient boosting machine classiﬁer (LGBM)—with 1DCNN. Recall, the F1 score, accuracy, and precision are some of the confusion metrics used to assess the effectiveness of the results.The results show that when used on reprocessed data, the proposed model performs best and is more than 98% accurate.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"24 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":"132402881","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

Advancement of Smart Healthcare Monitoring Systems in an Internet of Things-based Environment 物联网环境下智能医疗监控系统的发展

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s061

Durga Abhiram Gorle, Durga Sritha Dongla, Rishita Kakarlapudi, Naresh P

{"title":"Advancement of Smart Healthcare Monitoring Systems in an Internet of Things-based Environment","authors":"Durga Abhiram Gorle, Durga Sritha Dongla, Rishita Kakarlapudi, Naresh P","doi":"10.47392/irjash.2023.s061","DOIUrl":"https://doi.org/10.47392/irjash.2023.s061","url":null,"abstract":"With the growth of technology, there have been many improvements in people’s quality of life. New technologies have been implemented in the healthcare sector in one such area. Healthcare practitioners and experts are taking significant steps to use these emerging technologies to improve healthcare delivery signiﬁcantly. The IoT has been at the core of many emerging healthcare technologies, e.g., B. heartbeat sensors, EKGs, and blood pressure sensors, each having different microcontrollers that read data from the sensors, which can be interpreted as needed. Advantageously, healthcare services have become quite expensive for people. That being said, most people need help understanding how these advanced healthcare systems work. As a result, they have to rely on doctors to understand what is being inferred constantly. Therefore, to combat this increasing problem, we have developed a remote healthcare system that uses sensors to derive the patient’s vital signs and makes this data more accessible to the general public. Our primary focus was to work on a sim-pliﬁed mechanism to help the","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":"130027241","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

Evaluation of Blockchain Service Level Agreement (SLA) Using Hyperledger Fabric (HLF) 基于Hyperledger Fabric (HLF)的区块链服务水平协议(SLA)评估

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s013

D. K, Akoramurthy B, Surendiran B, Sivakumar T

{"title":"Evaluation of Blockchain Service Level Agreement (SLA) Using Hyperledger Fabric (HLF)","authors":"D. K, Akoramurthy B, Surendiran B, Sivakumar T","doi":"10.47392/irjash.2023.s013","DOIUrl":"https://doi.org/10.47392/irjash.2023.s013","url":null,"abstract":"Different sectors are being revolutionized by distributed ledger technology. According to the 2022 market valuation, Hyperledger is now the second-largest blockchain platform for smart contracts. The creation of numerous apps may be sped up and simpliﬁed with smart contracts, but there are certain draw-backs as well. For instance, vulnerability contracts are created intentionally to weaken candor, smart contracts are employed to conduct fraudulent activ-ities, and there are many redundant contracts that squander the efﬁciency of the system for no real reason. To solve these problems, we provide in this research Service Level Agreement(SLA) for Hyperledger smart contracts. We created Hyperledger smart contracts and focused on how smart contracts and consumers used data. By manually analyzing the transactions, we were able to extract four behavioral characteristics that may be used to differentiate between various contract types. Then, a smart contract is built using these to include 14 fundamental functionalities. We provide a data splitting algorithm for splitting the gathered smart contracts in order to create the experimental dataset. Then, we train and test our dataset using an LSTM network. The comprehensive experimental ﬁndings demonstrate that our method can discriminate between various contract types and may be used to identify malicious contracts and detect anomalies with acceptable precision, recall, and F1-score.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"33 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":"130645550","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

Multimodal Disease Prediction using Machine Learning and Deep Learning Techniques 使用机器学习和深度学习技术的多模态疾病预测

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s027

Akil Arsath J, S. S, Rakeshwaran S, Karthiga S

{"title":"Multimodal Disease Prediction using Machine Learning and Deep Learning Techniques","authors":"Akil Arsath J, S. S, Rakeshwaran S, Karthiga S","doi":"10.47392/irjash.2023.s027","DOIUrl":"https://doi.org/10.47392/irjash.2023.s027","url":null,"abstract":"Good health is man’s greatest possession but in today’s world people get a lot of diseases because of several reasons. The ability to predict diseases accurately is a critical aspect of healthcare. Machine learning techniques are increasingly being used to improve disease prediction. In this paper, we present a multi-disease prediction system that uses machine learning and deep learning algorithms to predict the likelihood of several common diseases. Even Though there are a lot of algorithms and techniques to predict a disease, there is no proper system to identify multiple diseases in a single system. Hence this paper focuses on the prediction of multiple diseases using machine learning and deep learning algorithms. Our aim is to build a model which efﬁciently predicts diseases such as kidney, heart and diabetes, malaria using machine learning and deep learning algorithms. This helps to make a better prediction of disease. For accurate prediction we are going to use stacking and ensembling models which help to increase the accuracy of the model. We are going to implement all these models in ﬂask web application.","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"23 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":"123848062","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 Scoping review of Data Storage and Interoperability in Blockchain based Electronic Health Record’s (EHR) 基于区块链的电子健康记录(EHR)中数据存储和互操作性的范围审查

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s018

Divyashree D, C. Ravi

{"title":"A Scoping review of Data Storage and Interoperability in Blockchain based Electronic Health Record’s (EHR)","authors":"Divyashree D, C. Ravi","doi":"10.47392/irjash.2023.s018","DOIUrl":"https://doi.org/10.47392/irjash.2023.s018","url":null,"abstract":"In the current era of technological smart world blockchain technology has bought revolution in Electronic Health Record’s (EHR’s) data exchange, which is important within medical research and healthcare. The healthcare industries are overlooked with problems in secure data exchange and privacy protection. The scoping review aims to identify the Blockchain technology used in healthcare organization could help in addressing privacy and accessibility issues. The distributed ledger technology is integrated with IPFS-Interplanetary ﬁle system helps in accomplishing ﬁrm controllable blockchain-based Electronic Health Records (EHR) data exchange scheme. To share and save large health record ﬁles between healthcare institutions the Electronic Health Records (EHR) with IPFS-Interplanetary ﬁle system is a promising solution. The decentralized block storage and integrated Electronic Health Records (EHR) with Interplanetary File System (IPFS) achieve failure of accessing health records. The study designate that personal health documents and Electronic Health Reports are the bulk chosen areas, using distributed ledger technology. Interoperability, data integrity and authentication are the major concern need to be reﬁned by blockchain technology. The most used platforms in EHR blockchain are hyperledger fabric and ethereum. The study also inspects","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"1 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":"122165518","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

Block Chain Based Disk Space Rental System 基于区块链的磁盘空间租赁系统

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s021

S. R, S. S, Kamali K

{"title":"Block Chain Based Disk Space Rental System","authors":"S. R, S. S, Kamali K","doi":"10.47392/irjash.2023.s021","DOIUrl":"https://doi.org/10.47392/irjash.2023.s021","url":null,"abstract":"Now a day’s electronic devices such as computers, smart phones and cameras produce enormous volumes of data each day, which require more and more storage resources. In order to fulﬁll this necessity, cloud storage renting systems were created. Cloud storage renting disk space allows people to expand their storage capacity without having to buy and maintain additional hardware. It can help users save money on hardware and reduce the need for physical space in their home or ofﬁce. It can also be used to store large amounts of data in a secure and cost-effective manner. Renting disk space also allows for easier sharing of data between multiple users, making collaboration easier and faster Cloud storage renting disk space allows people to expand their storage capacity without having to buy and maintain additional hardware. It can help users save money on hardware and reduce the need for physical space in their home or ofﬁce. Another issue with such systems is lack of trust.To overcome these problems we use block chain technology in disk rental system. This system is designed to be a peer-to peer services where users can rent out disks to each other without the need for a third party immediately. We use the smart contracts which automate the rental process Here we used Proof-of-Work (PoW) consensus","PeriodicalId":244861,"journal":{"name":"International Research Journal on Advanced Science Hub","volume":"1 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":"129676859","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

Autism Spectrum Disorder Prediction by Bio-inspired Algorithm with Blockchain based Database 基于区块链数据库的仿生算法预测自闭症谱系障碍

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s056

A. S., W. Varuna

引用次数: 0

Research Oriented Reviewing of Quantum Machine Learning 量子机器学习研究综述

International Research Journal on Advanced Science Hub Pub Date : 2023-05-28 DOI: 10.47392/irjash.2023.s022

A. C, V. M, P. P

引用次数: 0