2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)最新文献_第8页

COVID-19 Prediction Using Time Series Models 利用时间序列模型预测COVID-19

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074595

Deepthi A R, I. M

{"title":"COVID-19 Prediction Using Time Series Models","authors":"Deepthi A R, I. M","doi":"10.1109/ICAC3N56670.2022.10074595","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074595","url":null,"abstract":"Real-time data has evolved to become an integral part of understanding events across different timelines. Machine Learning uses different varieties of algorithms to determine the relationship between sets of data spread across timelines, visualize the current situation, and forecast the future, which is the most important aspect. Due to the breakout of COVID-19, a novel coronavirus, the entire planet is currently experiencing a disastrous crisis. At this time, the SARS-CoV-2 virus has proven to be a possible hazard to human life. The ARIMA Model i.e., Autoregressive Integrated Moving Average is compared with Facebook’s Prophet and VARMAX model to foretell the future. The dataset is divided into the training and testing set. The size of the COVID-19 dataset is relatively small as it is a pandemic that occurred recently, due to which much of the data is used for training purposes and the last twelve days have been used for testing and validating the model. The model is trained and fits on the training data set. The algorithms are now ready to anticipate future forecasts after it has been tested and trained. The models also record the predicted and actual values, allowing them to improve their accuracy in the future. In this paper, the results of the ARIMA model are compared against Prophet and VARMAX which are other popular machine learning time series models. For the ease of visualization of covid trends, a dashboard is built using Python’s Plotly and Dash and has been deployed using Voila.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"1 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":"131248108","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

Detection of diabetic Retinopathy using Retinal Fundus Images 利用视网膜眼底图像检测糖尿病视网膜病变

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074340

Lalitha Krishnasamy, Rajesh Kumar Dhanaraj, Monika Gupta, Priti Rai, K. Sruthi, Gopika T

{"title":"Detection of diabetic Retinopathy using Retinal Fundus Images","authors":"Lalitha Krishnasamy, Rajesh Kumar Dhanaraj, Monika Gupta, Priti Rai, K. Sruthi, Gopika T","doi":"10.1109/ICAC3N56670.2022.10074340","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074340","url":null,"abstract":"Diabetic retinopathy is one of the diabetes consequences that affects the eyes. This is caused by damage to the blood vessels in the retina, the light-sensitive tissue in the rear of the eye. It may create no symptoms at first, or it may cause minor eyesight difficulties. When the blood vessels become damaged, they may leak and this leakage can cause dark spots on our vision. The DR can be detected by finding the Hard Exudate present in it. The deep networks are becoming deeper and more complex. So that adding more number of layers to a neural network can make it stronger for image related tasks. But the main disadvantage in adding more layers is that, it may greatly reduces the accuracy of the image and also the data models are complex. In order to overcome this drawback, Recurrent Neural Network can be introduced. The fundamental benefit of using a recurrent neural network is that it can represent a collection of data in such a way that each pattern may be presumed to be reliant on the one before it. It can process inputs of any length. Even if the input size is large, the model size will not change. It makes the training process faster and attains more accuracy while compared to other neural networks. This method greatly reduces the loss of accuracy because each layer knows the information of the top layers while updating the weights. This Recurrent Neural Network has more number of parameters , so it is obvious that it can produce better result as compared to other net.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"1 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":"129277696","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

Design and Analysis of High Speed RISC Processor Using Pipelining Technique 基于流水线技术的高速RISC处理器设计与分析

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074423

Avanish Pratap Singh, Anushka Rai, Ashutosh Rajput, P. Joshi, Amrit Prakash

引用次数: 0

Lung cancer detection using scan images 肺癌扫描图像检测

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074331

Kartik Kumar, Shivank Srivastava, Aanchal Vij

{"title":"Lung cancer detection using scan images","authors":"Kartik Kumar, Shivank Srivastava, Aanchal Vij","doi":"10.1109/ICAC3N56670.2022.10074331","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074331","url":null,"abstract":"Lung cancer is one of the nation’s most horrible diseases. Early recognition and medication, on the other hand, could save lives. Despite the fact that CT scan scanning is the finest way to take pictures in the medical sector It is difficult for physician to discover and identify cancer on T images. As a result, computer-assisted diagnostics may help doctors accurately identify cancer cells. Numerous computer assistants who integrate imaging and machine learning algorithms have been researched and applied. The main idea behind this study was to explore the different-different computer-assisted techniques, analyze the best current method and identify their limitations and their constraints and finally propose a new model that upgrades the best available model. The approach used here is for lung cancer monitoring techniques to be classified as well as ranked as per their quality of diagnosis. Strategies are analyzed at each step and the overall scope, barriers are identified. It has been discovered that some people have low accuracy while others have great accuracy but are not close to 100 percent. As an outcome, our research hopes to enhance reliability to 99 percent.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"16 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":"126735088","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

Intelligent system of labor market regulation based on the evolutionary modeling of employment 基于就业演化模型的智能劳动力市场调控系统

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074149

Akhatov Akmal Rustamovich, Nurmamatov Mekhriddin, Nazarov Fayzullo, Munish Sabharwal

引用次数: 0

Predict the Game Analysis of Cricket Match Winning Using K-Nearest Neighbor and Compare Prediction Accuracy Over Support Vector Machine 基于k近邻的板球比赛获胜预测分析，并比较支持向量机的预测精度

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074193

R. Y. Rajesh, G. Sindhu

引用次数: 0

A Comparative Study of Artificial Intelligence based Vehicle Classification Algorithms used to Provide Smart Mobility 基于人工智能的车辆分类算法的比较研究

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074282

Prarthana V, Sushma Narayan Hegde, Sushmitha T P, Savithramma R M, R. Sumathi

{"title":"A Comparative Study of Artificial Intelligence based Vehicle Classification Algorithms used to Provide Smart Mobility","authors":"Prarthana V, Sushma Narayan Hegde, Sushmitha T P, Savithramma R M, R. Sumathi","doi":"10.1109/ICAC3N56670.2022.10074282","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074282","url":null,"abstract":"Due to the rising number of vehicles on the road and the limited resources supplied by current infrastructures, traffic problems are becoming more prevalent. Signalized junctions are the prime locations of congestions where commuters need to wait for long time in front of the signals to get their turn to move. This leads to several issues including wastage of time, additional fuel consumption, and green gas emissions. Optimization of traffic signals based on traffic behavior is widely explored topic in which vehicle detection and classification is one of the leading areas of research of Intelligent Transportation System (ITS). Among the technologies Artificial Intelligence (AI) has emerged as a giant in which vehicle classification has developed as a prominent subject of study because of its usefulness in several applications such as traffic control and surveillance, security systems, traffic congestion, avoidance, and accident prevention. Numerous algorithms and techniques for classifying vehicles have been proposed and implemented so far globally which mimics human intelligence. The goal of the paper is to familiarize the reader with the existing AI-based vehicle classification algorithms and to give a comparison of various vehicle detection and classification methods. The existing vehicle classification algorithms are summarized under two categories based on input type i.e., image or video. When the technologies such as AI, image processing, data mining and sensors are combined, the ITS can observe the road, initiate autonomous vehicle detection and thereby control traffic on road efficiently.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"28 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":"122538029","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

Task Migration in Volunteer Computing Systems 志愿计算系统中的任务迁移

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074085

Ehab Saleh, C. Shastry

{"title":"Task Migration in Volunteer Computing Systems","authors":"Ehab Saleh, C. Shastry","doi":"10.1109/ICAC3N56670.2022.10074085","DOIUrl":"https://doi.org/10.1109/ICAC3N56670.2022.10074085","url":null,"abstract":"Volunteer Computing is the use of underutilised computing power donated by volunteers who want to participate in ongoing high-throughput scientific projects. Due to the general simplicity of this concept, this type of computing attracts thousands of volunteers from all over the world. Many of them, however, leave the network, prompting the main server to initiate Task Migration, which involves transferring the remaining job to another volunteer’s device on the network. In this paper, we conduct two experiments in the task migration procedure in peer-to-peer volunteer network. In the first experiment, the server starts the migration procedure when it detects the first available volunteer, whereas in the second one, the server starts the migration after all of the server’s sub-peers have completed their jobs. To ensure the network’s heterogeneity, we select the dataset GWA-T-13 Materna, which contains performance metrics described as trace files of over 1500 VMs from the distributed Materna Data Centers in Dortmund, Germany. In both experiments, we compare the total execution time of the entire task and the maximum execution time that a peer can have to complete its assigned work. The simulation results show that in the second experiment, the main task was completed in less time than in the first experiment.","PeriodicalId":342573,"journal":{"name":"2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N)","volume":"25 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":"123076435","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

An Optimized Waveform Synthesis Scheme To Resolve High PAPR In MIMO OFDM Systems (A Review) 一种解决MIMO OFDM系统中高PAPR的优化波形合成方案(综述)

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074365

Qazi Saeed Ahmad, Imran Khan

引用次数: 0

Human behaviour analysis and face detection using machine learning 使用机器学习的人类行为分析和人脸检测

2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N) Pub Date : 2022-12-16 DOI: 10.1109/ICAC3N56670.2022.10074045

A. Dohare, Megha Sharma, Ravi Sahnker Pathak

引用次数: 0