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

Compact Cross Elliptical Patch Antenna with Wideband Characteristics for IOT Applications 具有物联网应用宽带特性的紧凑型交叉椭圆贴片天线

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596321

Namrata Choudhary, Harsh Malhotra, Naresh Kumar, Manish Sharma

引用次数: 1

A Study on Regression Models for Diabetes using WEKA 基于WEKA的糖尿病回归模型研究

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596269

Arjun Taneja, Ginni Arora, A. Rana

引用次数: 0

Analyzing Trend Probability and Risk Estimation of Rainfall Pattern over Maharashtra 马哈拉施特拉邦降雨模式趋势概率分析及风险估计

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596217

Shwena Goyal, Neetu Mittal, A. Rana

{"title":"Analyzing Trend Probability and Risk Estimation of Rainfall Pattern over Maharashtra","authors":"Shwena Goyal, Neetu Mittal, A. Rana","doi":"10.1109/icrito51393.2021.9596217","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596217","url":null,"abstract":"In meteorology, the prediction and risk analysis of rainfall is one of the foremost concerns. Early prediction of weather has acquired consideration by numerous scientists from different exploration networks because of its impact to the worldwide human existence. The arising profound learning strategies somewhat recently combined with the wide accessibility of huge climate perception information and the approach of data and computer technology innovation have inspired numerous researchers to investigate hidden hierarchical patterns in the enormous volume of climate dataset for climate determining. Several work and many techniques have already been carried out and proposed to predict rainfall. The focus is especially on statistical analysis, machine learning and deep learning techniques to analyze the data and forecast. The study explores profound learning strategies for climate determining. Specifically, proposed the expectation execution of LSTM and ANN models with respect to rain fall prediction. Those models are tried utilizing climate dataset. Forecasting precision of each model is assessed. The consequence of this study expected to add to climate gauging for wide application spaces including flight route to horticulture, the travel industry and early predication of rainfall.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"10 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":"126874700","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

Breast Cancer Recurrence Prediction Model Using Machine Learning Technique: State of the Art, Challenges and Future Direction 使用机器学习技术的乳腺癌复发预测模型:现状、挑战和未来方向

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596179

Mohan Kumar, S. Khatri, M. Mohammadian

{"title":"Breast Cancer Recurrence Prediction Model Using Machine Learning Technique: State of the Art, Challenges and Future Direction","authors":"Mohan Kumar, S. Khatri, M. Mohammadian","doi":"10.1109/icrito51393.2021.9596179","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596179","url":null,"abstract":"Nowadays, the most common type of cancer in women worldwide is Breast Cancer (BC). BC may be detected at early stage itself using Mammograms, probably before it's spread. Recurrent BC could occur months or years after initial treatment. Cancer may occur in the same place or spread to different areas due to local or distant recurrence. Early-stage treatment is done not only to cure BC but additionally facilitate in preventing its recurrence/ repetition. In predicting the early stage of BC, a machine learning (ML) technique has been used by most of the researcher. so, the present study we focus on a review of different ML techniques which predicts the recurrence of BC and identified the issues over the past decades. Also summarized the obtained results by the researcher for evaluating their predictive model performance. The study scope, results, merits, and demerits of earlier studies have been discussed. Later, gives deep insights of learning technique and then recommended a possible solution for further improvement for BC recurrence prediction.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"120 20 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":"126314020","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

Smart Healthcare Monitoring System Using Wireless Body Area Network 基于无线体域网络的智能医疗监控系统

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596360

Medini Gupta, Sarvesh Tanwar, A. Rana, Himdweep Walia

{"title":"Smart Healthcare Monitoring System Using Wireless Body Area Network","authors":"Medini Gupta, Sarvesh Tanwar, A. Rana, Himdweep Walia","doi":"10.1109/icrito51393.2021.9596360","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596360","url":null,"abstract":"The world population is increasing day by day and number of chronic diseases are on rise. Through Internet of Things (IoT) enabled devices such as Wi-Fi, Bluetooth-LE, health professionals can change the way they detect the illness and provide innovative ways for treatment. Real-time monitoring with smart sensors can save many lives during medical emergency. Wireless Body Sensor Network (WBSN) are widely used to monitor psychological parameters of an individual such as temperature, heart rate, electrocardiogram (ECG), brain activity and other vital symptoms. Smart Sensors are embedded in a smart watch which continuously monitors the patient's vital signs and data is delivered to smart phone in real time. If any of the psychological parameters fluctuates then an alert message is delivered to the hospital so that preventive measure can be taken. Doctors can provide medical consultation to their patients no matter how far they are located through remote healthcare monitoring. All the data is stored on the cloud that can be referenced anytime to learn the medical history of the patient This can lead to increase in quality of life. This paper examines the research work carried out on Wireless Body Sensor Network for real-time monitoring of user's psychological parameters which provide valid and reliable information.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"5 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":"121822745","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: 6

A Novel Technique to Detect the Hotspots in Swine Flu Effected Regions 猪流感疫区热点检测新技术

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596422

P. Nagaraj, A. K. Prasad

引用次数: 2

Secret Image Share hiding using Steganography 秘密图像共享隐藏使用隐写术

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596092

Anil Kumar, Priyanka Dahiya, Garima

引用次数: 0

Integrating Web Server Log Forensics through Deep Learning 通过深度学习集成Web服务器日志取证

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596324

Nidhin Nazar, V. Shukla, Gagandeep Kaur, Nitin Pandey

{"title":"Integrating Web Server Log Forensics through Deep Learning","authors":"Nidhin Nazar, V. Shukla, Gagandeep Kaur, Nitin Pandey","doi":"10.1109/icrito51393.2021.9596324","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596324","url":null,"abstract":"The world of Cyber Forensics is often filled with gigantic amounts of information, often more than what you would get from engagements in other branches of forensics. This not only makes the engagement much more thrilling for forensic experts, it also makes it much more tedious and a huge time-consuming factor when it comes to analysis. There are several tools available both from the open-source community and private devs, but not much from the fields of Artificial Intelligence (AI). Deep Learning, being at the core of Artificial Intelligence, will provide us with much better and more refined processing and predictions based on the available data. The setbacks and the breakthrough of using Deep Learning in Cyber Forensics are more or less the same as in every other branch, where AI is used to solve tasks critical to a person, or most of the time, crucial to an organization. To start with, for Deep Learning to be integrated with the fields of Cyber Forensics, i.e., after an incident, it must also be trained in the areas of Cyber Security, or to be exact, in Cyber Defense, i.e., before an incident. This idea is pretty intuitive. This paper looks at Deep Learning models as much similar to the most complex structure in the known universe, the human brain. After all, these models have been inspired and based on the human brain. This paper attempts to find existing solutions on how to best implement a Deep Learning model in the fields of Cyber Forensics and proposed how Deep Learning models could help the world of Cyber Security, especially for the IR teams.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"10 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":"130051061","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

Web mapping spatial data information analysis using the Free Open Source Software Server Service (FOSSSS) 基于自由开源软件服务器服务(FOSSSS)的Web地图空间数据信息分析

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596519

Vimal Shukla, J. Sarup, Vipin Rai

{"title":"Web mapping spatial data information analysis using the Free Open Source Software Server Service (FOSSSS)","authors":"Vimal Shukla, J. Sarup, Vipin Rai","doi":"10.1109/icrito51393.2021.9596519","DOIUrl":"https://doi.org/10.1109/icrito51393.2021.9596519","url":null,"abstract":"Free Open Source Software server Service (FOSSSS) is computer software that anyone can use, modify, and distribute without restriction. Many people or organizations contribute to open source software, which is provided under licenses that follow the Open Source Definition. This study to represent the how to manipulate and visualization of map based application using open source server like GeoServer. This study also interacts with web solution of GIS applications using different Free Open Source Software server (FOSSS) solutions. Low cost, great stability and security are all benefits of open server software, which handling mini and medium sized web based GIS application projects prefer it as a result. An efficient WebGIS system is presented in this research. The area of GIS has grown at a rapid pace in recent decades, and it now includes both proprietary and open source GIS software. After introducing the essential principles of WebGIS, it chose open-source technologies such as Apache Tomcat, GeoServer, and PostGIS. Finally, discussion on how to integrated web based GIS small application.","PeriodicalId":259978,"journal":{"name":"2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)","volume":"39 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":"126897571","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

Audio Detection using Mel-frequency Cepstral Coefficients 使用mel频率倒谱系数的音频检测

2021 9th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO) Pub Date : 2021-09-03 DOI: 10.1109/icrito51393.2021.9596443

Uppu Jithendra, Usha Mittal, Priyanka Chawla

引用次数: 0