2021 5th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第2页

IP Traffic Classification of 4G Network using Machine Learning Techniques 基于机器学习技术的4G网络IP流量分类

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418397

Rahul, Amit Gupta, A. Raj, Mayank Arora

{"title":"IP Traffic Classification of 4G Network using Machine Learning Techniques","authors":"Rahul, Amit Gupta, A. Raj, Mayank Arora","doi":"10.1109/ICCMC51019.2021.9418397","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418397","url":null,"abstract":"In today's world, the number of internet services and users is increasing rapidly. This leads to a significant rise in the internet traffic. Thus, the task of classifying IP traffic is essential for internet service providers or ISP, as well as various government and private organizations in order to have better network management and security. IP traffic classification involves identification of user activity using network traffic flowing through the system. This will also help in enhancing the performance of the network. The use of traditional IP traffic classification mechanisms which are based on inspection of packet payload and port numbers has decreased drastically because there are many internet applications nowadays which use port numbers which are dynamic in nature rather than well-known port numbers. Also, there are several encryption techniques nowadays due to which the inspection of packet payload is hindered. Presently, various machine learning techniques are generally used for classifying IP traffic. However, not much research has been conducted for the classification of IP traffic for a 4G network. During this research, we developed a new dataset by capturing packets of real-time internet traffic data of a 4G network using a tool named Wireshark. After that, we extracted the inferred features of the captured packets by using a python script. Then we applied five machine learning models, i.e., Decision Tree, Support Vector Machines, K Nearest Neighbours, Random Forest, and Naive Bayes for classifying IP traffic. It was observed that Random Forest gave the best accuracy of approximately 87%.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126139808","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

Teaching-Learning Based Optimization of Dual Watermarking of Color Images 基于教学的彩色图像双水印优化

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418382

Sivananthamaitrey. P, P. R. Kumar

引用次数: 0

Water Conservation Control by using IoT Smart Meter 利用物联网智能水表实现节水控制

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418251

L. S. Sairam Nadipalli, D. Sai Akhil, A. A. Kumar, N. Ganesh

引用次数: 4

Social Distance Identification Using Optimized Faster Region-Based Convolutional Neural Network 基于优化的更快区域卷积神经网络的社会距离识别

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418478

S. K., B. S, Palangappa M B

{"title":"Social Distance Identification Using Optimized Faster Region-Based Convolutional Neural Network","authors":"S. K., B. S, Palangappa M B","doi":"10.1109/ICCMC51019.2021.9418478","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418478","url":null,"abstract":"In 2019, an aggressive coronavirus disease (COVID-19) has resulted in large-scale epidemic with its deadly outbreak in more than 190 countries and nearly 114 million confirmed cases as of February 2021, along with 2.52 million deaths worldwide. As no proper vaccinations are available, the only viable solution to fight this pandemic is physical distance or social distancing. Reducing the spread of COVID-19 in public areas, and to reduce the rate of losing helpless lives, social distancing is a primary and primitive proposed approach by the World Health Organization (WHO). In shopping malls, organizations, schools and other covered areas, the government and national healthcare authorities have set a 2-meter or 6-foot social distance in their surroundings as a required safety precaution. It is tough for authorities to manage people manually, whether the individuals maintain social distancing in public and crowded areas. Keeping this as our motivation, this research work proposes a simplified and optimized way to achieve social distancing detection between the individuals and notifying the higher officials if it is not maintained properly. This paper proposes OFRCNN -optimized faster region-based convolutional neural network methodology, which runs in real-time and is built using a Faster Region-Based Convolutional Neural Network (Faster R-CNN), which is used for object detection and COCO dataset is used for training.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114951697","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: 11

Design and Implementation of PLC based water Curtain Nozzle Controller for Warehouse Application 基于PLC的仓库水幕喷头控制器的设计与实现

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418307

S. Sangamithra, S. Sakitha, R. Rajasree, T. Joby Titus

引用次数: 0

Transfer Learning for Detection of COVID-19 Infection using Chest X-Ray Images 利用胸部x线图像检测COVID-19感染的迁移学习

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418398

Nikhil Bhatia, Geetanjali Bhola

{"title":"Transfer Learning for Detection of COVID-19 Infection using Chest X-Ray Images","authors":"Nikhil Bhatia, Geetanjali Bhola","doi":"10.1109/ICCMC51019.2021.9418398","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418398","url":null,"abstract":"Coronavirus is a contagious disease that affects individuals in a large scale. Coronavirus had a huge impact on the nation’s economy and human lifestyle. The motivation behind this study was establishing a better diagnosis test for coronavirus infection. The RT-PCR test is used to diagnose the coronavirus frequently and returned a negative result for an infected individual. Furthermore, this test remains prohibitively expensive for most citizens, and not everyone could afford it due to financial hardship. An efficient imaging approach is de veloped for the evaluation of lung conditions, which has been done by examining the chest X-ray or chest CT of an infected person. Deep Learning is the well-suited sub domain of Artificial Intelligence [AI] technology, which offers helpful examination to consider more number of chest X-rays images that can basically have an effect on coronavirus screening. The goal of this research is to cluster the radiograph images present in the dataset into COVID-19, healthy and viral pneumonia by making use of the artificial neural networks. The training dataset was fine-tuned with eleven previously trained convolutional neural architectures. The assessment of the models on a test sample shows that AlexNet, DenseNet-121, GoogleNet and Squeezenet1.1 as the top performing models.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129414106","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: 3

A Survey on: Personality Prediction from Multimedia through Machine Learning 基于机器学习的多媒体个性预测研究综述

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418384

B. Singh, Mansi Katiyar, Shefali Gupta, Nikam Gitanjali Ganpatrao

{"title":"A Survey on: Personality Prediction from Multimedia through Machine Learning","authors":"B. Singh, Mansi Katiyar, Shefali Gupta, Nikam Gitanjali Ganpatrao","doi":"10.1109/ICCMC51019.2021.9418384","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418384","url":null,"abstract":"The prediction of the personality of an individual is a critical problem in both areas whether it is considered in the context of organizations or in the case of our daily lives. Prediction of personality depends on many factors and these factors may vary from one individual to another.Personality prediction is identifying the personalities of individuals through their actions in different situations and observing their behaviours in various circumstances. Personality traits show the different characteristics of different people based on their thoughts, feelings, and behaviours. There can be positive as well as negative personality traits. Personality traits are based on the Big Five Model also known as the OCEAN model i.e. Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. In the previous study, many investigations has been done. They have used different techniques and different algorithms to predict the personality of different people. Some have used handwriting to predict personality using the GSC algorithm. Facial expressions have been used in some studies using CNN features. Few studies have focused on the social networking sites for personality prediction by examining an individual’s reaction to different posts, their comments, their posts, etc. One study predicted personality using AU, LF, POS, Emotional features and their combinations. Apart from this, there are few limitations in these single models discussed above. They work efficiently for only a small dataset but on increasing the size of the dataset their accuracy keeps decreasing. Multimodal is effective in this case and to make the task automatic, an intelligent multimodal agent can identify personality traits better based on both verbal and non-verbal features.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129529592","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

Investigation of Machine Learning Assistance to Education 机器学习对教育的辅助研究

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418364

Megha Gupta, Gunjan Batra

引用次数: 0

Comparative Analysis of Localization Techniques Used in LBS LBS中定位技术的比较分析

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418232

Mahar Kenan

引用次数: 1

Crime Investigation using DCGAN by Forensic Sketch-to-Face Transformation (STF)- A Review 基于法医素描-人脸变换(STF)的DCGAN犯罪侦查综述

2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2021-04-08 DOI: 10.1109/ICCMC51019.2021.9418417

S. Nikkath Bushra, K. Uma Maheswari

{"title":"Crime Investigation using DCGAN by Forensic Sketch-to-Face Transformation (STF)- A Review","authors":"S. Nikkath Bushra, K. Uma Maheswari","doi":"10.1109/ICCMC51019.2021.9418417","DOIUrl":"https://doi.org/10.1109/ICCMC51019.2021.9418417","url":null,"abstract":"This paper outlines about the most advanced technique of Artificial Intelligence for digitally ascertaining a criminal through facial recognition system by converting forensic sketch into a real photo using Deep Convolutional Generative Adversarial Network (DCGAN). Suppose a crime act is reported to a cop as an eyewitness by an individual by remembering certain set of facial features of an illicit and trying to imitate it in the form of hand drawn sketch based on the given information. The forensic sketch is pictured by an expert based on the verbal explanation given by a person after commitment of crime by a perpetrator. The rough sketch is given as an input to train the neural network and after several epochs the network quickly learns and generates a scrupulous realistic facial image of a suspect from the forensic sketch. This is very much helpful in crime investigations to obtain several such real photographs of a suspect from forensic sketches easily with precise details within a short period of time. This is an amazing practice that can produce real facial images of high resolution color photos from a low quality sketches which is incomplete or partial in nature with different pose variations like color, tone etc. It is very much useful in domains like forensics, law enforcement, Facial recognition system and security and authentication systems.","PeriodicalId":131747,"journal":{"name":"2021 5th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128476304","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