2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)最新文献_第6页

A Review on Data Offloading Paradigms in Internet of Things (IoT) 物联网(IoT)数据卸载范式综述

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074597

Nidhi, J. Kumar

引用次数: 0

Covid-19 Pandemic Predictive System Using Machine Learning 使用机器学习的Covid-19大流行预测系统

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074050

Swati Sharma, V. Sharma, Rohit Aggarwal, Rashmi Gupta

引用次数: 0

Machine Learning and 5G Charging Function with Network Analytics Function for Network Slice as a Service 机器学习和5G收费功能，网络切片即服务的网络分析功能

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074433

M. Bhavsar, P. Deshmukh, Khushal Khairnar

{"title":"Machine Learning and 5G Charging Function with Network Analytics Function for Network Slice as a Service","authors":"M. Bhavsar, P. Deshmukh, Khushal Khairnar","doi":"10.1109/ICAC3N56670.2022.10074433","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074433","url":null,"abstract":"5g system is more customer centric which give very high throughput, low latency, highly scalable, customer industry driven technology. 5G system has charging function which generate session and event based information from Session Management Function (SMF) and Access and mobility management function (AMF). The standard for advance use cases for 5G by incorporating network element/services like Network Data Analytics Function (NWDAF), Network Slice Management Function (NSMF) are defined in Third Generation Partnership Project (3GPP) release 15 and 16. These efforts are to make 5G use cases more customers driven, industry driven and make more analytical Key target of this project to incorporate machine learning techniques on the data available through NWDAF, NSMF and NAMF (Service-based Interface for Access and Mobility Management Function). This makes operator to launch potentially consumed charging use cases specifically to use Network Slice as a Service (N-SaaS). With the use of Machine Learning (ML) and Artificial Intelligence (AI) algorithms, data can be modelled to predict the customer charging model, predictive analysis to avoid future outages, optimal use of resources and traffic forecasting which gives operator potentially high revenue and of course customer satisfaction for better service.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125707229","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

Emoji Classification using Random Forest Classifier 使用随机森林分类器的表情符号分类

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074460

Madhu Bala, Meenu Gupta, Rakesh Kumar

引用次数: 0

Comparative Analysis of Recommendation Systems based on Medical Data Sets 基于医疗数据集的推荐系统比较分析

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074148

Ravi Kumar Barwal, Neeraj Raheja

{"title":"Comparative Analysis of Recommendation Systems based on Medical Data Sets","authors":"Ravi Kumar Barwal, Neeraj Raheja","doi":"10.1109/ICAC3N56670.2022.10074148","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074148","url":null,"abstract":"In today’s world, a number of most common diseases such as DM (Diabetes Mellitus) for which not assured medicine has searched yet, the capable method for these types of patients for the survival is to take care and proper diet. Fasting Blood Sugar is one of the vital parameters of diabetes mellitus. In the health care system, numerous data of the patients have analyzed that help to obtain insights and assist the estimate of the diseases. Hence, there is a need for an intelligent scheme for estimation of the health situation by analyzing the standard of living, health check reports, and communal activities. However, the recommendation system is becoming the main framework for health care applications. Moreover, fitness intelligent schemes have become a necessary tool in the decision-making approach in health areas. Conversely, people use an online system for understanding the physical condition. Therefore, health recommendation schemes have estimated better results in diagnosis, medical insurance, medical-based management techniques, and other medicine based on the health profile of the patient. This paper provides comparative analysis of various recommendation methods such as MLP, RNN, LSTM, SVM, LR, and NB. These recommendation methods are used for the recommended diseases with Medical Data Sets.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125779835","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

Social Media Mining For Suicidal Ideation 社交媒体挖掘自杀意念

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10073980

Siddhant Satya, Rajni Jindal

引用次数: 0

Local Regression Based Real-Time Traffic Sign Detection using YOLOv6 基于YOLOv6的局部回归实时交通标志检测

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074236

Ravinder Kaur, J. Singh

{"title":"Local Regression Based Real-Time Traffic Sign Detection using YOLOv6","authors":"Ravinder Kaur, J. Singh","doi":"10.1109/ICAC3N56670.2022.10074236","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074236","url":null,"abstract":"Since it involves both classifying and Logisticising objects in a scene, object detection is considered one of the most challenging topics in computer vision. While YOLOv6 is an improved version of the original You Only Look Once model, it is also among the most cutting-edge deep neural network (DNN)-based object identification methods available today. DNNs have recently been proven to attain more extraordinary object identification performance than previous approaches. However, even without a strong GPU, YOLOv6 is still exceedingly fast as compared to its previously released versions and can decide the driving course approximately in real-time. Hence, YOLOv6 is suited in applications to certain embedded systems and smartphones as well which have a major underlying constaints of power usage. To improve traffic sign identification in real time, we are using YOLOv6 and an improved Logistic Regresssion (LR) based classifier in this research. The LR classifier here is used to identify traffic sign classes. We have used the Indian Traffic Sign Detection Benchmark Dataset (ITSDBD) is used to train and evaluate the network whose results are then compared with similar systems proposed in the past.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124667959","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 Comparative Statistical Analysis Between ML Algorithms & DNN Techniques Using MNIST Dataset 使用MNIST数据集的ML算法和DNN技术的比较统计分析

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074302

Akshit Rajan Rastogi, Chelsea Verma, Divya Sharma, P. Goyal

{"title":"A Comparative Statistical Analysis Between ML Algorithms & DNN Techniques Using MNIST Dataset","authors":"Akshit Rajan Rastogi, Chelsea Verma, Divya Sharma, P. Goyal","doi":"10.1109/ICAC3N56670.2022.10074302","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074302","url":null,"abstract":"Handwritten digit recognition has been around since a very long time and it has always been a topic of attention among the students and researchers. This job of recognizing handwritten content has great importance as it helps in recognizing various type of important information which are filled by hand but are not clearly understood. While solving this problem, the most common challenge is that the digits written by hands are of different size, orientation or thickness. Inspite of all these challenges, various Machine Learning Algorithms & Deep Neural Network Techniques are trying harder to achieve higher accuracy. In this report, we have tried to compare the accuracies of most common and popular ML Algorithms which includes SVM (Support Vector Machine), Random Forest Classifier (RFC) & KNN (K-Nearest Neighbour) with DNN Techniques (Deep Neural Network Technique) also termed as CNN (Convolutional Neural Network) using Keras. We have applied these algorithms and techniques on MNIST dataset. With the help of the results obtained, we have plotted some graphs to show differences between ML (Machine Learning Algorithms) & DNN (Deep Neural Network Techniques). In this research work, we got the accuracy of approx 97.86% using SVM, 97.10% using KNN, 97.05% using RFC while on the other hand, by using CNN, we got 99.98% accuracy on validation image data. Also, we were able to achieve accuracy approx , 96.85% using RFC, 97.73% using SVM, 96.80% using KNN while on the other hand, by using CNN, we got 98.72% accuracy on test image data.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124822096","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 Prediction Based Approaches to Improve Diagnostic Accuracy for BreastCancer 使用基于预测的方法提高乳腺癌的诊断准确性

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074203

Palak, Kamaljit Singh Saini

引用次数: 1

Cloud Security 云安全

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074139

Pallav Raj, Ravi Shankar Kumar, Avneesh Kumar

引用次数: 0