2022 6th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第9页

An Efficient Association Rule Mining from Distributed Medical Database for Predicting Heart Disease 分布式医学数据库中一种有效的关联规则挖掘方法用于心脏病预测

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753720

Aswin Kumar.K, S. Gowri, John Wilifred David .J, Y. Bevish Jinila

{"title":"An Efficient Association Rule Mining from Distributed Medical Database for Predicting Heart Disease","authors":"Aswin Kumar.K, S. Gowri, John Wilifred David .J, Y. Bevish Jinila","doi":"10.1109/ICCMC53470.2022.9753720","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753720","url":null,"abstract":"Naïve Bayes classification categorization in machine learning is employed to check the patient's entire heart illness in this proposed work. As a result, the percentage of patients that contract disease as both positive and negative data is used. Most database management systems and desktop analytics and visualization applications make working with big data difficult. As a result of this machine learning can be employed from the standpoint of data mining, and the proposal displays a machine learning methodology. The classifiers are used to process heart percentages, and the results are given as a confusion matrix. In the presence of a training dataset, a unique classification strategy is introduced that can effectively increase classification performance. Heart disease stent diagnostic In addition, the generated method has a high identification of rates, making It's a useful tool for junior cardiologists to check the cardio vascular patients with a high risk for certain diseases and refer them to expert cardiologists for further evaluation.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125281520","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

Non-Linear Non-Gaussian Gaussian and Seventh-Order Volume Kalman Filter Algorithm and Its Modeling Application 非线性非高斯高斯和七阶体积卡尔曼滤波算法及其建模应用

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753827

Zhengrong Liu

引用次数: 1

Performance Analysis of Squeezenet and Densenet on Fetal Brain MRI Dataset 挤压网和致密网在胎儿脑MRI数据集上的性能分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753874

P. S., Sharvanthika K S, Nidhi Bohra, S. S.

引用次数: 3

Intelligent Application of Virtual Reality Technology in the Design of Elderly Service Station 虚拟现实技术在老年服务站设计中的智能应用

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753872

Yantao Wang

引用次数: 1

FPGA Implementation of Area and Speed Efficient CORDIC Algorithm 面积和速度高效CORDIC算法的FPGA实现

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753730

Harshita Nair, Anu Chalil

{"title":"FPGA Implementation of Area and Speed Efficient CORDIC Algorithm","authors":"Harshita Nair, Anu Chalil","doi":"10.1109/ICCMC53470.2022.9753730","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753730","url":null,"abstract":"This paper proposes an efficient serial and parallel Coordinate Rotation Digital Computer (CORDIC) architecture that is both area utilization and delay efficient and compares the two architectures. CORDIC algorithm is an integral part of DSP (digital signal processing) applications since it helps to perform complex operations such as trigonometric, logarithmic, exponential, and many other mathematical functions with a multiplier less architecture and using simple hardware blocks. In this project 32-bit floating-point serial and parallel CORDIC architecture is implemented on Field programmable gate array device (FPGA) with the help of different adders such as Carry Save adder (CSA), Carry Select adder (CSLA), Han Carlson adder, Sklansky and Ladner Fischer adder in place of the conventional ripple carry adder block used in CORDIC architecture to come up with an area and speed efficient CORDIC architecture. The proposed architecture with Ladner Fischer adder gives 4.7 percent area utilization improvement compared to other parallel prefix adders in serial CORDIC architecture and parallel CORDIC architecture. It also gives 43.5 percent lesser delay compared to serial CORDIC architecture implemented with Carry save adder and 43.9 percent lesser delay than parallel CORDIC architecture implemented with carry-save adder.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126364841","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

Theoretical Analysis on Blind Detection Method of Shortwave Communication Electronic Signal Based on Wireless Network 基于无线网络的短波通信电子信号盲检测方法理论分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754106

Ying Wang

引用次数: 0

Predictive Analytics on Covid-19 Prediction using ResNets 基于ResNets的Covid-19预测分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9754134

S. Vadivel, R. Jayakarthik

引用次数: 0

Cardiovascular Disease Prediction using Enhanced Support Vector Machine Algorithm 基于增强支持向量机算法的心血管疾病预测

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753916

N. Manjunathan, S. Girirajan, D. Jaganathan

{"title":"Cardiovascular Disease Prediction using Enhanced Support Vector Machine Algorithm","authors":"N. Manjunathan, S. Girirajan, D. Jaganathan","doi":"10.1109/ICCMC53470.2022.9753916","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753916","url":null,"abstract":"Cardiovascular syndrome is a distinct disorder which remains as the core cause of morbidity and mortality in people all over the world. It is a deadly disease that affects a significant portion of the world's population. When deaths and the proportion of persons affected by heart disease are considered, it dearly signifies the importance of early identification of cardiovascular illness. Traditional diagnostic methods are insufficient for this condition. Prediction of heart infection is one of the most important issues in clinical data analysis. In the healthcare business, there is a wealth of information. Developing a medical diagnosis system for heart disease diagnosis using machine learning models provides more precise test than the previous method. All the available Machine learning techniques (MLTs) have proved to be assistive in making decisions, predicting illness in the huge amounts of data that are available in healthcare data domains. Numerous studies purely graze the apparent using models to prognosticate cardiac syndrome. The proposed study offers a strategy for identifying key features using MLT, which augment the accuracy of predicting the diseases present in the heart. Different sets of methods and techniques with proficient machine learning algorithms are used to identify the diseases at the early stages itself. The proposed research study has obtained a higher degree of performance with high accuracy by using a composite process to produce a statistical method for heart disease.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131009336","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

Controller Design for Dead Time Approximated Model of Juice Extraction Unit of Sugar Factory 糖厂榨汁装置死区时间逼近模型控制器设计

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753728

S. Sunori, Govind Singh Jethi, S. Arora, Amit Mittal, F. Khan, P. Juneja

引用次数: 1

Analyzing Accuracy of Road Accident Dataset based on Fatality Rate 基于死亡率的道路交通事故数据集精度分析

2022 6th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2022-03-29 DOI: 10.1109/ICCMC53470.2022.9753804

M. Ramalingam, P. Yogavelu, S. Yamuna, M. Siddarth

{"title":"Analyzing Accuracy of Road Accident Dataset based on Fatality Rate","authors":"M. Ramalingam, P. Yogavelu, S. Yamuna, M. Siddarth","doi":"10.1109/ICCMC53470.2022.9753804","DOIUrl":"https://doi.org/10.1109/ICCMC53470.2022.9753804","url":null,"abstract":"Street mishaps are most likely the most important reason influencing unexpected interaction of people and monetary resulting in property exploitation. Street well-being is associated with the preparation and execution of certain techniques to combat street and vehicle collisions. Examining street mishap data is an important way to separate several variables associated with street mishaps that contribute to lowering the mishap rate. The collection of street mishap data is a significant challenge in street safety study. On another street mishap data, this research study uses latent class clustering (LCC) and the k-modes grouping approach in our assessment. The goal of employing both strategies is to determine which strategy works better. The standards created for each cluster will not demonstrate any group examination method better. Nonetheless, it is sure that the two strategies are appropriate to eliminate heterogeneity of street mishap information. This research study uses LCC, k-means clustering procedure in processing the street mishap information and shape various groups. Further, Frequent Pattern (FP) development procedure is applied on the clusters shaped and entire data processing system (EDS). The standards created in groups and EDS demonstrates that the diversity exist in whole informational index and clustering before investigation, which unquestionably lessens heterogeneity from the informational collection and gives better arrangements.","PeriodicalId":345346,"journal":{"name":"2022 6th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128319091","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