2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)最新文献

Design and Comparison of Tumor Segmentation Using an ML-Based Clustering Method 基于ml聚类方法的肿瘤分割设计与比较

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987435

V. Samudrala, N. Revathi, S. Padhi, S. Sasireka, B. Selvalakshmi, Divya Francis

{"title":"Design and Comparison of Tumor Segmentation Using an ML-Based Clustering Method","authors":"V. Samudrala, N. Revathi, S. Padhi, S. Sasireka, B. Selvalakshmi, Divya Francis","doi":"10.1109/I-SMAC55078.2022.9987435","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987435","url":null,"abstract":"A brain tumor is a common syndrome, where a specific set of cells gather and begin to grow inside a human brain, to interfere with the brain s regular function. Though there are a lot of techniques that act as a preliminary test for tumors, an analysis of the MRI scan image is sometimes enough to predict the presence of the tumor. This study aims in finding the best machine learning algorithm that can detect brain tumors with the highest accuracy value. For this purpose, a dataset of images from MRI scans of human brain s is obtained via Kaggle. After that, this dataset is preprocessed using a few techniques. The techniques involve image scaling and color conversion. Two different machine learning models were produced by two different algorithms. The machine learning algorithms used in this work are the U-net and the FPN. The created models are then trained using the preprocessed datasets. The models are then evaluated using a separate set of photos after training. Two metrics, the IoU and dice coefficient, are used to analyze the training and validation results. Although the parameters for both models remain the same during training and validation, it was ultimately determined that the FPN method is more effective at predicting brain cancers. The algorithm’s ultimate IoU value is 0.865, and its dice coefficient is 0.9034. The model is complete because the results were excellent for an image processing model. Real-time photos are used to test the model one more time before it is finished. This analysis’ findings are also deemed to be exceedingly adequate.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121271574","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

A Novel Approach for IoT Intrusion Detection System using Modified Optimizer and Convolutional Neural Network 一种基于改进优化器和卷积神经网络的物联网入侵检测新方法

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987314

S. Vijayalakshmi, T. D. Subha, L. Manimegalai, Ektha Sudhakar Reddy, Dama Yaswanth, Sakithya Gopinath

{"title":"A Novel Approach for IoT Intrusion Detection System using Modified Optimizer and Convolutional Neural Network","authors":"S. Vijayalakshmi, T. D. Subha, L. Manimegalai, Ektha Sudhakar Reddy, Dama Yaswanth, Sakithya Gopinath","doi":"10.1109/I-SMAC55078.2022.9987314","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987314","url":null,"abstract":"The development of cyber security is very important, and as a result, it has received a significant amount of research interest from academic institutions and industrial groups all over the globe. It is also of the utmost importance to offer computing that is environmentally friendly for the Internet of Things. In order to detect intrusions and identify malicious actors, machine learning algorithms play an essential part in the cyber security of the internet of things (IoT). Because of this, the purpose of this work is to create novel techniques of extracting attributes that take use of the benefits offered by swarm intelligence (SI) method. We devise a technique for the extracting the attributes that is based on the traditional neural networks. In addition, in order to compute the effectiveness of the IDS method that was created, four well recognized public datasets were employed. We also evaluated detailed comparisons to many alternative optimization approaches in order to test the proposed method’s ability to compete successfully in the market. The findings demonstrate that the created strategy performs very well when measured against a variety of assessment metrics.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125344496","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

Implementation of Cyber Security for Enabling Data Protection Analysis and Data Protection using Robot Key Homomorphic Encryption 利用机器人密钥同态加密实现数据保护分析和数据保护的网络安全

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987407

Ankur Biswas, A. Karan, Nidhi Nigam, H. Doreswamy, Serikkhan Sadykanova, Mangazina Zhanel Rauliyevna

{"title":"Implementation of Cyber Security for Enabling Data Protection Analysis and Data Protection using Robot Key Homomorphic Encryption","authors":"Ankur Biswas, A. Karan, Nidhi Nigam, H. Doreswamy, Serikkhan Sadykanova, Mangazina Zhanel Rauliyevna","doi":"10.1109/I-SMAC55078.2022.9987407","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987407","url":null,"abstract":"Cloud computing plays major role in the development of accessing clouduser’s document and sensitive information stored. It has variety of content and representation. Cyber security and attacks in the cloud is a challenging aspect. Information security attains a vital part in Cyber Security management. It involves actions intended to reduce the adverse impacts of such incidents. To access the documents stored in cloud safely and securely, access control will be introduced based on cloud users to access the user’s document in the cloud. To achieve this, it is highly required to combine security components (e.g., Access Control, Usage Control) in the security document to get automatic information. This research work has proposed a Role Key Homomorphic Encryption Algorithm (RKHEA) to monitor the cloud users, who access the services continuously. This method provides access creation of session-based key to store the singularized encryption to reduce the key size from random methods to occupy memory space. It has some terms and conditions to be followed by the cloud users and also has encryption method to secure the document content. Hence the documents are encrypted with the RKHEA algorithm based on Service Key Access (SKA). Then, the encrypted key will be created based on access control conditions. The proposed analytics result shows an enhanced control over the documents in cloud and improved security performance.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115261333","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

Machine Learning based Sales Prediction and Characterization using Consumer Perceptions 使用消费者感知的基于机器学习的销售预测和表征

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987359

J. Sreemathy, N. Prasath

{"title":"Machine Learning based Sales Prediction and Characterization using Consumer Perceptions","authors":"J. Sreemathy, N. Prasath","doi":"10.1109/I-SMAC55078.2022.9987359","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987359","url":null,"abstract":"In today’s age of automated scenarios and digital lifestyle, online shopping has really made its way to everyone’s household, with one touch anyone can order the required products. The use of digital marketing over conventional marketing is often favored. It is beneficial to both social media marketing professionals and technicians. When conducting research, one may gain preliminary insights into consumers’ perceptions of social media advertisements and online buying habits. Online knowledge exchange allows researchers, academics, and business people to swiftly and easily connect with individuals while conducting searchable mobile brand website research. This research provides a methodical description of a study that only aids consumers in making the optimal smartphone decision for their own parametric needs. A given dataset will be examined utilising machine learning methods, such as brand name predictions with regression and precise results. Groups of people are frequently paid by brands to create internet evaluations, which may be favourable to them or unfavourable to their competitors.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122571573","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

Women Safety and Alertness in Instagram using Deep Learning 在Instagram上使用深度学习的女性安全和警觉性

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9986500

S. Nissi, K. G. Saravanan, C. Srivenkateswaran, Nishathini, D.C. JullieJosephine, S. Shibia Malar

引用次数: 0

Establishment of Soil Preferential Flow Model based on Modern Remote Sensor Observation Methods 基于现代遥感观测方法的土壤优先流模型的建立

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987286

Yan Liu

引用次数: 0

Research on Intelligent Real time Monitoring System based on Neural Network Optimization 基于神经网络优化的智能实时监控系统研究

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987336

Changhui Wang

引用次数: 0

Analysis of Feature Extraction and Waveform Matching from the Perspective of Multi-Dimensional Information Integration Algorithm 多维信息集成算法视角下的特征提取与波形匹配分析

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987295

Hong Zhang

引用次数: 0

Modelling a Risk-based Network Model for Epileptic Seizure Prediction using Learning Approaches 利用学习方法建立基于风险的癫痫发作预测网络模型

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987399

Anandaraj A, P. Alphonse

{"title":"Modelling a Risk-based Network Model for Epileptic Seizure Prediction using Learning Approaches","authors":"Anandaraj A, P. Alphonse","doi":"10.1109/I-SMAC55078.2022.9987399","DOIUrl":"https://doi.org/10.1109/I-SMAC55078.2022.9987399","url":null,"abstract":"The process of developing across space and time in the networks of a person with epilepsy occurs through Epileptic seizures. The generalizable technique is developed in this research to predict a particular patient seizure using the evaluation of featurerepresentation to obtain the features from the signals of multichannel EEG. The features are revealed for the signals of EEG using the available parameters. The features are input to the Risk-based Elman learning model (r - ELM) to evaluate feature representation to collectively train the data. The suggested model of r-ELM obtains 0. 096/h as the rate of false prediction, 85% as sensitivity, and 10% as the time in warning to perform the tests from the EEG dataset of CHB-Mn scalp using 10 patients. The suggested method has superiority over the existing results. Various metrics are used in the experiment which shows the epileptic stage as the essential factor affecting seizures’ performance. A subject-oriented method for seizure prediction is presented in the proposed system, which is powerful for the unbalanced data and created for any dataset of scalp EEG with no requirement of subject-oriented engineering.","PeriodicalId":306129,"journal":{"name":"2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130393993","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

Multi-Center Backup Framework based on Audio and Video Complex Information Extraction Algorithm 基于音视频复杂信息提取算法的多中心备份框架

2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) Pub Date : 2022-11-10 DOI: 10.1109/I-SMAC55078.2022.9987347

Han Wu

引用次数: 0