2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)最新文献_第8页

Identification And Classification Of Brain Tumor From MRI Using Transfer Learning Approach 应用迁移学习方法从MRI中识别和分类脑肿瘤

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037223

O. R. Devi, C. Bindu, E. S. Kumar

引用次数: 0

Analysis on Various Clamping Models of Square Shaped Diaphragm in Capacitive Pressure Sensor for Intra Ocular Pressures 电容式眼压传感器中方形膜片的各种夹持模式分析

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037593

Kavitha Jagabathuni, Swapna Peravali

引用次数: 1

GIS based Urban Water Distribution Network Analysis: A Case Study in Kochi, India 基于GIS的城市配水网络分析:以印度高知市为例

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037629

K. V. Nibi, M. Nitin Kumar, A. R. Devidas, M. Ramesh, Shyju P. Thadathil

{"title":"GIS based Urban Water Distribution Network Analysis: A Case Study in Kochi, India","authors":"K. V. Nibi, M. Nitin Kumar, A. R. Devidas, M. Ramesh, Shyju P. Thadathil","doi":"10.1109/ICCCIS56430.2022.10037629","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037629","url":null,"abstract":"Water distribution systems are one of the critical infrastructures of urban communities. Uneven water distribution can cause intermittent and inadequate water supply to the urban population. Therefore, it is imperative to study the uneven water distribution for the water demand of the urban community (SDG6). In this work, a GIS-based model is developed to characterize the demand-supply variations of an Urban community. As the case study, this paper presents the modeling and digitization of a real-world water distribution network in Kochi, India. QGIS is the network modeling platform with the QGISRed plugin, which relays on EPANET. A geo-referenced water distribution network map is used to model the network accurately. The base demand for each junction has been identified using GIS algorithms for the modeled real water network. Results show that the simulator has been able to elicit the characteristic of the water network and accurately quantify the parameter metrics as per the real-world scenario. The 24-hour extended EPANET simulation identifies the critical areas of Edakochi, where the water distribution network has very low or negative pressure. The paper also proposes three strategies for rectifying uneven water distribution, such as increasing the input volume of water supply, an additional water connection from another water resource, and introducing an overhead tank in the study area. Results show that all these three methods can enhance the water supply and mitigate the low-pressure points in the modeled water network","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116635266","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

Decentralized Data Privacy Protection and Cloud Auditing Security Management 分布式数据隐私保护与云审计安全管理

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037676

M. Mageshwari, R. Naresh

{"title":"Decentralized Data Privacy Protection and Cloud Auditing Security Management","authors":"M. Mageshwari, R. Naresh","doi":"10.1109/ICCCIS56430.2022.10037676","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037676","url":null,"abstract":"Decentralized data protection is becoming more important as more firms employ Cloud resources. Securing, protecting, and processing user data are primary issues that Cloud Computing faces. This study’s primary goal is to detect and address attack protection in Cloud. Our objectives are to comprehend the present state of cloud computing security concerns and methods, identify future cloud computing security concerns to offer countermeasures for potential. Preventative measures to employing cloud services include data security and privacy concerns. The challenge is to create cloud platforms for integrating decentralized information systems to ensure the user’s privacy. For management units of distributed systems, the requirements analysis yielded a model for organizational levels of cloud systems. By bypassing the single-point-of-failure of TPA, our suggested approach may prevent service disruption and privacy-preserving concerns. The extensive security analysis proves that our suggested solution meets all the needed security criteria. We also implement our suggested method with PSO-Homomorphic Algorithm (PSO-HA) and evaluate its efficiency in real-world situations, demonstrating its efficacy, high efficiency, and portability. Our results show that our methodology for simultaneously-integrated recovery can be implemented in polynomial time and is thriving.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123867028","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

Automated Estimation of Fault Locations in Bipolar HVDC Systems Employing Artificial Neural Networks 基于人工神经网络的双极直流系统故障位置自动估计

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037680

Sudhir Singh, P. Lakra

{"title":"Automated Estimation of Fault Locations in Bipolar HVDC Systems Employing Artificial Neural Networks","authors":"Sudhir Singh, P. Lakra","doi":"10.1109/ICCCIS56430.2022.10037680","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037680","url":null,"abstract":"With a continuous escalation in demand of power, the Indian Electrical system is in constant demand for long transmission lines to fulfil its requirement due to extremely distributed demand and generation location. Advanced HVDC system is one such possibility that finds its utility, especially during long-distance transmission. Such electrical transmission systems are prone to short circuit faults, which subsequently leads to a large current, which will eventually harm or damage the system’s equipment. Thus, the system requires a quick restoration in order to re-establish power transmission and assure system safety. Hence, this paper presents a model, which can precisely assess the location of the fault in a Bipolar HVDC system. The model provides accurate results which is also collectively optimal. A Bi-polar transmission line which is 814 km long and operates at 700 kV, 1500 MW is developed on PSCAD/EMTDC software based on CIGRÉ benchmark guidelines. The designed model is further simulated for short circuit fault with fault ON resistance of 0.01 Ω and fault OFF resistance of 1.0 x 106 Ω with varying fault location along transmission line at an interval of 1 km. The acquired data is collected and processed for feature extraction. Data from both the ends of the transmission line is used for training and testing of deep neural network models. The evaluation of the proposed system has been done based on the mean squared error and accuracy of fault estimation. It is shown that the proposed system outperforms contemporary baseline approaches.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122362210","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

An Effective Phishing Site Prediction using Machine Learning 利用机器学习进行有效的网络钓鱼网站预测

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037744

A. Pandey, Tushar Sharma, S. Basnet, Ankesh Kumar, Dr. Sonia Setia

引用次数: 0

A Chaotic Encrypted Reliable Image Watermarking Scheme based on Integer Wavelet Transform-Schur Transform and Singular Value Decomposition 基于整数小波变换-舒尔变换和奇异值分解的混沌加密可靠图像水印方案

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037672

Anurag Tiwari, V. K. Srivastava

{"title":"A Chaotic Encrypted Reliable Image Watermarking Scheme based on Integer Wavelet Transform-Schur Transform and Singular Value Decomposition","authors":"Anurag Tiwari, V. K. Srivastava","doi":"10.1109/ICCCIS56430.2022.10037672","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037672","url":null,"abstract":"In the present era of the internet, image watermarking schemes are used to provide content authentication, security and reliability of various multimedia contents. In this paper image watermarking scheme which utilizes the properties of Integer Wavelet Transform (IWT), Schur decomposition and Singular value decomposition (SVD) based is proposed. In the suggested method, the cover image is subjected to a 3-level Integer wavelet transform (IWT), and the HH3 subband is subjected to Schur decomposition. In order to retrieve its singular values, the upper triangular matrix from the HH3 subband’s Schur decomposition is then subjected to SVD. The watermark image is first encrypted using a chaotic map, followed by the application of a 3-level IWT to the encrypted watermark and the usage of singular values of the LL-subband to embed by manipulating the singular values of the processed cover image. The proposed scheme is tested under various attacks like filtering (median, average, Gaussian) checkmark (histogram equalization, rotation, horizontal and vertical flipping) and noise (Gaussian, Salt & Pepper Noise). The suggested scheme provides strong robustness against numerous attacks and chaotic encryption provides security to watermark.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130098547","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 Study of Deep Learning Techniques on Oilseed Crops 油料作物的深度学习技术研究

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037740

Sweety Sehgal, A. Roy

引用次数: 0

A Novel Text Resemblance Index Method for Reference-based Fact-checking 一种基于参考文献的事实核查文本相似索引方法

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037728

Y. Barve, Jatinderkumar R. Saini

{"title":"A Novel Text Resemblance Index Method for Reference-based Fact-checking","authors":"Y. Barve, Jatinderkumar R. Saini","doi":"10.1109/ICCCIS56430.2022.10037728","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037728","url":null,"abstract":"As in electronic era, data is transmitted via social network and web, people are harmed by false and deceptive content, such as misinformation. A fact-checker will examine specific indicators of falsity to determine the veracity of a piece of content. To perform automated fact-checking, retrieving information from the web, cleaning the contents, and using machine learning techniques are required. Prior research has focused on linguistic and literary characteristics as well as approaches based on similarity measurements. All the details and intricacies of the problem are not adequately covered by any of the papers referenced in the resource. We advanced a Text Resemblance Index (TRI) algorithm with a veracity-scanning model for the purpose of automating fact-checking URLs in the healthcare industry. To execute fact-checking in a journalistic manner, a set of innovative content, domain-specific, and sentimental scores based on polarity are applied. The Text Resemblance Score (TRS), a newly generated feature, outscored comparable properties with an accuracy of 88.27%, according to a thorough analysis of the proposed approach in contrast to traditional distance measures. In comparison to the Jaccard distance-based algorithm accuracy of 75.56% when leveraging an algorithm, TRI showed enhanced accuracy of 90%. Compared to the prior study, the TRS feature-based technique produced an accuracy improvement of 2.40%.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129556576","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

Analyzing fashion trends using CNN and Cloth classification with respect to season and state 使用CNN和布料分类分析季节和状态的时尚趋势

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037748

D. Shubhangi, Baswaraj Gadgay, Priyanka Jagannath Nandyal, M. A. Waheed

{"title":"Analyzing fashion trends using CNN and Cloth classification with respect to season and state","authors":"D. Shubhangi, Baswaraj Gadgay, Priyanka Jagannath Nandyal, M. A. Waheed","doi":"10.1109/ICCCIS56430.2022.10037748","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037748","url":null,"abstract":"Machine learning now does have a broad aspect of apps in a variety of fields. Deep learning methods, particularly convolution neural networks (CNN), are frequently used to analyse visual imagery. CNN main applications include face recognition, image recognition, object recognition, and so on. As the use of machine learning in many industries grows rapidly around the world, the fashion industry is following suit. The proposed model describes the creation of a computer vision system for clothing detection and classification in e-commerce images. The architectures used in this work for detection and classification are YOLO v3 and Residual Networks, respectively. We are training and testing the clothes detection and classification networks using a portion of the Fashion image dataset, which contains box annotations for clothing location, as well as manually collected data. The proposed models detect clothing using bounding boxes. The dataset consists of 8 different classes with 500 images per class. Investigational outcomes show that, as anticipated, CNN algorithms are the most effective and efficient network configurations for clothing detection and classification. Following testing, it was discovered to have 90% accuracy. In addition, Indian, Western, and Indo-Western cuisines are classified by state and season.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129750730","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