2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)最新文献_第3页

Analysis of Social Engineering Attack on Cryptographic Algorithm 针对密码算法的社会工程攻击分析

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596568

Shubham Gupta, Isha, Anando Bhattacharya, Himanshu Gupta

引用次数: 3

Education and Gender Empowerment 教育和性别赋权

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596110

Navpreet Kaur, Priyanka Chawla

引用次数: 0

Comprehensive Study: Machine Learning & Deep Learning Algorithms for Paddy Crops 综合研究:水稻作物的机器学习和深度学习算法

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596189

K. Anandhan, A. S. Singh, K. Thirunavukkarasu, Dr. Raju Shanmugam

{"title":"Comprehensive Study: Machine Learning & Deep Learning Algorithms for Paddy Crops","authors":"K. Anandhan, A. S. Singh, K. Thirunavukkarasu, Dr. Raju Shanmugam","doi":"10.1109/icrito51393.2021.9596189","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596189","url":null,"abstract":"Agriculture is a backbone of our Indian country economy. One of the basic needs is food for every human in the world. An Indian farmer's generally plan the whole cultivation process based upon a traditional method or own experience. The advanced technology will lead to help the farmers in order to take proper guidance of whole cultivation process and achieve better yield. Nowadays in the digital world generates a various large amount of useful information, it is a really difficult task to store and process on a meaningful way. Another trending research area such as different intelligent machine learning techniques are used to help the farmer in order to learn from machine learning model. The pesticide paradox testing will help the plant growth properly. There are many paddy leaf diseases attack the plant at early stage, due to that yield will get reduced. In our research paper, we analyze various rice disease classifications, segmentation and provide an accuracy level using different machine learning techniques (ML), deep Learning (DL) models.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133593604","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: 4

Adaptable Intelligent Models for Pulmonary Tuberculosis Detection and Classification 肺结核检测与分类的自适应智能模型

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596084

Abdul Karim Siddiqui, V. Garg

引用次数: 0

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596405

Y. Kumar, H. Sharma, Ritu Pal

{"title":"Popularity Measuring and Prediction Mining of IPL Team Using Machine Learning","authors":"Y. Kumar, H. Sharma, Ritu Pal","doi":"10.1109/icrito51393.2021.9596405","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596405","url":null,"abstract":"The Indian Premier League (IPL) is a Twenty20 cricket league held in India each year between March and May. Eight teams participating from Indian cities or states. The Board of Control in India (BCCI) started the league in 2007. The Indian Premier League (IPL) is the most popular cricket league in the world, ranking sixth among all sports leagues in terms of average appearance in 2014. The IPL was the first sporting event in the world to be broadcast live on YouTube in 2010. Since the IPL is so common, In order to be more competitive, it is necessary to assess how people will react to the league. Machine Learning techniques can be used to resolve the problem of predicting outcomes. Public opinion, as well as the causes behind it, has been discovered to be political. Among the many social media channels available, one of the popular social service websites is Twitter, which allows users to post events from their daily lives. 7 lakh People's feedbacks are taken from the IPL-2020 Twitter website using Application Interface. This paper is split into two sections. First, we divided 7 lakh tweets into different teams based on hashtag attributes, analyzed people's feelings in neutral, positive, and negative, checked the most popular team during IPL-2020, and measured accuracy using Multinomial Naïve Bayes, Logistic Regression, Ridge Classifier, Random Forest, SGD Classifier, and Decision Tree on those tweets. In the second part, 50k data were collected at random from 7 lakh tweets and F1-score, precision, accuracy, and recall was measured using Multinomial Naïve Bayes, Logistic Regression, Ridge Classifier, Random Forest, SGD Classifier, and Decision Tree. This paper aims to correctly assess people's feedback for an event such as the Indian Premier League 2020.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128818408","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

Impact of Emerging Technologies on Future Mobility in Smart Cities by 2030 新兴技术对2030年智慧城市未来交通的影响

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596095

Sheeba Hansain, Deepika Gaur, V. Shukla

引用次数: 2

Anomaly Detection in Crowded Places: Review 拥挤场所的异常检测:综述

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596229

Neha Jain, Himani Bansal

引用次数: 3

Home Automation using Smart Devices and IoT 使用智能设备和物联网的家庭自动化

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596533

Shruti Dash, P. Choudekar

引用次数: 8

Internet of Thing based Electrical Device Surveillance and Management Apparatus 基于物联网的电气设备监控与管理设备

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596180

Saurabh Singh Rajawat, Abdul Basit, Himdweep Walia, Komal Saxena, A. Rana

{"title":"Internet of Thing based Electrical Device Surveillance and Management Apparatus","authors":"Saurabh Singh Rajawat, Abdul Basit, Himdweep Walia, Komal Saxena, A. Rana","doi":"10.1109/icrito51393.2021.9596180","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596180","url":null,"abstract":"Internet of Things (IoT) has revolutionized the way of living. The word “automatic” can be seen come into the practice with the advent of IoT. Humans and interact with devices and devices can interact with humans and also with each other. this has made life exceptionally easy. we are now surrounded by Smart Cities, Smart Devices, Smart Cars, and likewise through the IoT. Along with the advantages, come few limitations as well. The major limitation of interconnecting and establishing communication between the devices is the power consumption. Being part of a developing nation, this limitation becomes all the more challenging. The purpose of discussing the Energy-saving from Electrical Device Scrutiny and Control systems based on the Internet of Things is imperative because a hefty amount of energy is disbursed by lighting appliances, so making enhanced proficiency and hasty fault detection device may be a substantial challenge. To overwhelm this matter, appropriate energy-saving procedures and lighting control are to be executed. In the proposed model, we have two types of models which approaches are tracked counting on the character of application for on-premise ranges with narrowed buildings IEEE 802.11n wireless technology is active where all the appliances are connected with a standard Wi-Fi network. In the other model have related to the street lamp with a hefty number of devices connected only in a single wired way, a wired configuration is hired to avoid range issues.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123902532","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: 2

Plant Leaf Disease Diagnostic System Built on Feature Extraction and Ensemble Classification 基于特征提取和集成分类的植物叶片病害诊断系统

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596070

N. Kaur, V. Devendran

{"title":"Plant Leaf Disease Diagnostic System Built on Feature Extraction and Ensemble Classification","authors":"N. Kaur, V. Devendran","doi":"10.1109/icrito51393.2021.9596070","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596070","url":null,"abstract":"Plants are a major source of energy for humans and animals alike. Plant leaves are the most common way for plants to communicate with the atmosphere. As a result, academics and academicians are responsible for investigating the problem and developing ways for recognizing disease-infected leaves. Farmers all across the world will be able to take immediate action to avoid their crops from getting severely damaged, so sparing the world from a potential economic crisis. Because manually detecting diseases may not be the ideal solution, a robotic methodology for detecting leaf ailments could benefit the agriculture industry while also enhancing crop output. The goal of this study is to improve classification outcomes by combining ensemble classification in conjunction with hybrid Law's mask, Gabor, SIFT, GLSM and LBP. The method proposed exemplifies the usage of ensemble classification. For comparison purpose Gabor and SIFT are utilized. The features employed are also vital in attaining the best results because ensemble classification has demonstrated to be more accurate. The experiments used sick leaf pictures of three plant types from the PlantVillage.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124240492","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