2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)最新文献_第9页

Transaction fee forecasting in post EIP-1559 Ethereum using 1-D Convolutional Neural Network 基于一维卷积神经网络的EIP-1559后以太坊交易费用预测

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176712

Harshal Shridhar Kallurkar, B. R. Chandavarkar

{"title":"Transaction fee forecasting in post EIP-1559 Ethereum using 1-D Convolutional Neural Network","authors":"Harshal Shridhar Kallurkar, B. R. Chandavarkar","doi":"10.1109/ICSCCC58608.2023.10176712","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176712","url":null,"abstract":"Cryptocurrencies have established their identity as a healthy alternative to the maintenance of digital assets. Their applications include low-cost money transfers and yield farming. Ethereum is a blockchain that provides the functionality of doing more than a transaction regarding cryptocurrency. Ether is the default cryptocurrency of Ethereum, which is issued to the miners after the successful completion of the consensus mechanism to avoid fraudulent miners gaining profits. Transactions in Ether require that the user should include what is called a “fee” besides the amount that is sent by the user. The EIP-1559 (Ethereum Improvement Proposals) upgrade to the Ethereum protocol has substantially changed how the transaction fee is calculated. Since this transaction data can be considered time-series data, many prior approaches have been proposed to forecast such a transaction fee using suitable methods effectively. One-dimensional Convolutional Neural Networks have recently been successfully applied to time-series forecasting problems, showing promising results. This paper proposes a univariate 1-D CNN for an effective forecast of transaction fees in the new Ethereum protocol. Furthermore, this paper also compares the proposed method with existing standard approaches, and the results show the superior performance of simple 1-dimensional convolutional neural networks over existing hybrid models.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128836454","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

Lemon Diseases Detection and Classification using Hybrid CNN-SVM Model 基于CNN-SVM混合模型的柠檬病害检测与分类

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176828

Radhika Gupta, M. Kaur, N. Garg, H. Shankar, Suhaib Ahmed

{"title":"Lemon Diseases Detection and Classification using Hybrid CNN-SVM Model","authors":"Radhika Gupta, M. Kaur, N. Garg, H. Shankar, Suhaib Ahmed","doi":"10.1109/ICSCCC58608.2023.10176828","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176828","url":null,"abstract":"In many regions around the globe, the agricultural business is heavily dependent on the cultivation and production of lemons. Unfortunately, a number of diseases, including Lemon Scab, Septoria Spot, Sooty Mould, Armillaria, and Huanglongbing can adversely influence the yield and quality of the fruit as well as the growth of lemon trees. In order to stop the spread of these diseases and lessen their effects, there is a huge requirement for precise and effective techniques of identification and classification. In order to classify various lemon disorders, this study suggests a hybrid model that incorporates Support Vector Machines (SVM) and Convolutional Neural Networks (CNN). The suggested model makes use of a dataset that includes pictures of both healthy and infected lemon leaves, including those with Armillaria, Septoria Spot, Sooty Mould, and Huanglongbing. To broaden the dataset's diversity and size, the photos were pre-processed utilizing data augmentation techniques. The suggested model makes the most of both techniques by combining the best features of CNN for feature extraction and SVM for classification. The recommended hybrid model's functionality is assessed using a dataset of 4,821 orange pictures, and as a result, an accuracy of 89.6% is attained. As it offers a precise and effective strategy for analyzing the various lemon diseases, this model is a useful tool for the early detection and control of the spread of various diseases in lemon plants thus, enhancing the yield and quality of lemon fruit along with the sustainability concerning the agricultural sector.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116150726","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

Area-coverage path planning for unmanned aerial vehicles: A Review * 无人机区域覆盖路径规划研究综述*

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176527

Sanjiv Sonawane, Kunwar Pal

引用次数: 0

Software Cost Estimation: A Literature Review and Current Trends 软件成本估算:文献综述和当前趋势

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176495

Suneeta Singh, K. Kumar

引用次数: 0

Comparative Analysis of Face Detection Techniques on Videos of Low Vs High Quality 低质量视频与高质量视频的人脸检测技术对比分析

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176915

A. Mool, J. Panda, K. Sharma

引用次数: 0

Revolutionizing Rice Farming: Automated Identification and Classification of Rice Leaf Blight Disease Using Deep Learning 革新水稻种植:利用深度学习自动识别和分类水稻叶枯病

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176408

V. Kukreja, Rishabh Sharma, Satvik Vats

{"title":"Revolutionizing Rice Farming: Automated Identification and Classification of Rice Leaf Blight Disease Using Deep Learning","authors":"V. Kukreja, Rishabh Sharma, Satvik Vats","doi":"10.1109/ICSCCC58608.2023.10176408","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176408","url":null,"abstract":"Rice is considered a fundamental dietary component for a significant portion of the global population and is regarded as a crucial crop for ensuring food security on a global scale. Rice crops are susceptible to diverse diseases, among them rice leaf blight disease, which is instigated by the fungus Helminthosporium oryzae. The rice leaf blight disease has the potential to result in substantial reductions in crop yield and poses a significant risk to rice cultivation across various regions globally. The current study introduces a novel approach for the multi-classification of rice leaf blight disease utilizing a hybrid model that combines Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) techniques. The model is designed to classify the disease based on six distinct levels of severity. A dataset comprising 6000 images of the rice crop was gathered and subjected to pre-processing and augmentation techniques to enhance the model's efficacy. The proposed model attained a total accuracy of 95.25% in detecting and classifying rice leaf blight disease. Ablation studies were conducted to assess the respective contributions of the CNN and LSTM components toward the model's overall performance. Furthermore, a comparison was made among severity levels to determine the optimal severity level for diagnostic purposes. The model under consideration exhibits the capacity to function as a mechanism for the timely identification and mitigation of rice leaf blight disease, thereby leading to a substantial enhancement in agricultural productivity and guaranteeing food sustainability.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130392200","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

Development of Energy Efficient Routing Protocol using Genetic Algorithm for IoMT 基于遗传算法的IoMT节能路由协议开发

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176755

Rishabh Ranjan Jha, Manvendra Singh, Md. Sarfaraj Alam Ansari, Kunwar Pal, M. C. Govil

引用次数: 0

Fleet tracking and Geofencing using the Internet of Things (IoT) 使用物联网(IoT)的车队跟踪和地理围栏

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176660

M. M. Raikar, Kailash Angadi, Santosh Reddy, Nagaraj Naik, Abhilash Doddwada

引用次数: 0

Performance analysis of PSO for solving coverage problem in WSN PSO解决无线传感器网络覆盖问题的性能分析

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176720

Praneetha P Bhat, G. V.

引用次数: 0

EMG Feature Selection Approach to Improve Classification Accuracy — A Review 提高分类精度的肌电特征选择方法综述

2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2023-05-26 DOI: 10.1109/ICSCCC58608.2023.10176966

Shweta Agarwal, Raman Chadha, Bhoopesh Singh Bhati

{"title":"EMG Feature Selection Approach to Improve Classification Accuracy — A Review","authors":"Shweta Agarwal, Raman Chadha, Bhoopesh Singh Bhati","doi":"10.1109/ICSCCC58608.2023.10176966","DOIUrl":"https://doi.org/10.1109/ICSCCC58608.2023.10176966","url":null,"abstract":"Nowadays, many computing systems are a part of daily life; therefore, it is more comfortable to communicate with them naturally. The field of human-computer interaction (HCI) was created in order to break down the obstacles to human-computer communication. One of the types of HCI that is, Hand Gesture Recognition (HGR), which predicts the type of a certain hand action. The electrical activity of skeletal muscles is one potential input for these types of models. The purpose of movement produced by the human brain is communicated through electromyography (EMG) signals. In order to identify EMG data that is precise for any class, the most pertinent collection of EMG attribute values must be used to train a system. With the aid of a combination of machine learning and EMG data, this paper aims to present the most recent real-time feature selection techniques and classification algorithms in a comprehensive review of the literature. Finally, several gaps have been found that may point the way for fresh lines of inquiry in the field of EMG-based gesture detection, and a proposed approach for improving the overall classification accuracy of the EMG signal is presented.","PeriodicalId":359466,"journal":{"name":"2023 Third International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131824387","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