2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)最新文献_第8页

Performance of Three-Phase Induction Motor with Space Vector Pulse Width Modulation under Artificial Neural Network Control 空间矢量脉宽调制三相异步电动机在人工神经网络控制下的性能

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179695

A. Sahu, D. Joshi

引用次数: 0

Hesitant Triangular Fuzzy Dombi Operators and Its Applications 犹豫三角模糊Dombi算子及其应用

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179707

A. B, Vidhya. M

引用次数: 0

Development of Online Clearance System Using Web-Based System 基于web系统的在线通关系统开发

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179667

Abir AlSideiri, R. M. Tawafak, G. Alfarsi, B. Khudayer, Z. C. Cob

引用次数: 0

Identification of Malaria Disease Using Machine Learning Models 使用机器学习模型识别疟疾疾病

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179665

S. Kuzhaloli, S. Thenappan, Premavathi T, V. Nivedita, M. Mageshbabu, S. Navaneethan

引用次数: 0

Optimization techniques for preserving privacy in data mining 数据挖掘中保护隐私的优化技术

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179655

K. Devi, K. Balasamy, M. Prathyusha, R. Jeevitha, P. Balasubramanie, M. Eswaran

{"title":"Optimization techniques for preserving privacy in data mining","authors":"K. Devi, K. Balasamy, M. Prathyusha, R. Jeevitha, P. Balasubramanie, M. Eswaran","doi":"10.1109/ICECCT56650.2023.10179655","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179655","url":null,"abstract":"Data mining is one of the significant area where it plays a predominant role in extracting important factors and trends from large volume of data. This covers various areas such as healthcare, education, entertainment, finance, e-commerce applications etc., The data mining domain has used a variety of algorithms, including supervised, unsupervised, semi-supervised, and reinforcement learning techniques. Under healthcare arena, it deals with huge amount of sensitive data such as patients' data such as their name, age, health records. Those sensitive data have been utilized by the intruders for extracting the original data and also became a prey for the authorized access. Hence, the privacy is one of the serious concern that should be addressed. Various privacy preserving in data mining (PPDM) techniques such as anonymization, perturbation, condensation and cryptographic methods are available to protect those data. In this paper, the optimization techniques such as Genetic algorithm(GA) under evolutionary method and Particle swarm optimization(PSO) under meta heuristic method have been discussed and how it plays an important part in providing more optimal results by securing those sensitive and important information from the unauthorized access.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127672540","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

Sensitivity Analysis of Polarity Control Electrically doped GaAs-InAs Tunnel Field Effect Transistor for Bio-sensing Application 极性控制电掺杂GaAs-InAs隧道场效应晶体管生物传感灵敏度分析

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179770

Dharmender, Piyush Yadav, Rashi Gupta, Shivangi Singh

引用次数: 0

Analyzing Security and Privacy issues for Multi-Cloud Service Providers Using Nessus 分析使用Nessus的多云服务提供商的安全和隐私问题

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179727

T. Singh, Ajay Mahaputra Kumar

{"title":"Analyzing Security and Privacy issues for Multi-Cloud Service Providers Using Nessus","authors":"T. Singh, Ajay Mahaputra Kumar","doi":"10.1109/ICECCT56650.2023.10179727","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179727","url":null,"abstract":"Cloud computing security is a broad term that covers a wide range of security and privacy issues for businesses that use multi-cloud services. The service providers must take several factors into account when addressing security for their clients, including access and identity control, in-transit, and other security factors such as confidentiality, vulnerability management, threats, and audits. This paper takes a close look at each of these areas of cloud security and shows how multi-cloud service providers can protect themselves and move forward. It also talks about the problems with protecting systems that use more than one cloud and gives ways to deal with these problems. The reader should understand all of the security concerns that come with multi-cloud setups and how to deal with them in light of the latest cyber threats. The sole motivation of this paper is to raise awareness about multi-cloud service security in different aspects and its impact. Nessus, which is a well-known security tool, has been used to find vulnerabilities and other critical security concerns. Overall, experiments have been performed on three different websites: “www.cuchd.in”, “indiapost.gov.in” and “ajaykumar.in”. Despite this, the mitigation approaches for each vulnerability are explained systematically.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121327378","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

Performance And Security Enhanced Improved Hill Cipher 性能和安全增强改进希尔密码

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179696

Muralidharan D, B. R, Vijay Sai R, C. K

引用次数: 0

Machine Learning Approaches on Pedestrian Detection in an autonomous vehicle 自动驾驶车辆中行人检测的机器学习方法

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179836

V. Ranganayaki, Jency Rubia J, P. S. Ramesh, K. Rammohan, R.Babitha Lincy, A. Deepak

引用次数: 0

EEG evoked automated emotion recognition using deep convolutional neural network 脑电诱发深度卷积神经网络自动情绪识别

2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT) Pub Date : 2023-02-22 DOI: 10.1109/ICECCT56650.2023.10179711

Abgeena Abgeena, S. Garg

{"title":"EEG evoked automated emotion recognition using deep convolutional neural network","authors":"Abgeena Abgeena, S. Garg","doi":"10.1109/ICECCT56650.2023.10179711","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179711","url":null,"abstract":"As life continues to change in the digital era, it is crucial to perceive a person's emotional state. Affective computing is receiving more attention with the increase in the human-computer interface (HCI). Human emotion recognition employing electroen-cephalogram (EEG) signals has been studied to obtain a person's emotional status for different stimuli. However, it is difficult to identify clear patterns in EEG signals because they have low electrical impulses and are highly sensitive to noise. A deep convolutional neural network (DCNN) was employed in the present study to recognize emotions in EEG signals. For this purpose, a publicly available dataset, DREAMER, was utilized in this study to assess the applicability of the model for emotion classification. The dataset consisted of three-dimensional emotions, that is, valence, arousal, and dominance (VAD). 2D emotions arousal and valence were the most-recognized emotions in existing research. The present study identified the 3D emotions present in the above-mentioned dataset. In this study, raw EEG signals from the DREAMER dataset were pre-processed. Subsequently, three EEG rhythms, theta, alpha, and beta, were extracted using a bandpass filter. The power spectral density (PSD) was computed using fast Fourier transform (FFT) in the feature extraction. Finally, a 1D CNN model is applied to the classification of emotions. In addition, the performance of the proposed model was compared with two machine learning (ML) classifiers: random forest (RF) and extreme Gradient Boosting (XGBoost) classifiers. The highest accuracy (ACC) of 97.6% was obtained using the proposed model in the dominance dimension. The working principles were compared and discussed to determine the suitability of the model for emotion recognition applications.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128521571","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