G. Sowmya, K. Keerthi, J. T Lalitkrushna, S. Srividhya, Jothy Soman, M. Vanitha
{"title":"An Architecture for Efficient encoding of Quasi cyclic LDPC codes and its implementation in FPGA","authors":"G. Sowmya, K. Keerthi, J. T Lalitkrushna, S. Srividhya, Jothy Soman, M. Vanitha","doi":"10.1109/CSNT54456.2022.9787597","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787597","url":null,"abstract":"The Quasi Cyclic LDPC codes are one of the most widely used channel coding technique as they offer low complexity encoding along with parallelism in decoding. The existing architectures used for the encoding of such codes focus either on higher throughput or lower hardware resources. The proposed architecture optimizes both, especially for the implementation in space-qualified FPGAs where the resources are limited, yet higher throughput and encoding speed are expected. The proposed architecture can be used for any QC-LDPC code where the length of the information sequence is even multiple of the code’s Circulant size. As an illustration to the proposed architecture, an encoder for the CCSDS specified (8176, 7154) QC-LDPC codes is implemented in FPGA.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133087567","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}
R. Vairagade, Leela S. Bitla, Harshpal H. Judge, Shubham D. Dharpude, Sarthak S. Kekatpure
{"title":"Proposal on NFT Minter for Blockchain-based Art-Work Trading System","authors":"R. Vairagade, Leela S. Bitla, Harshpal H. Judge, Shubham D. Dharpude, Sarthak S. Kekatpure","doi":"10.1109/CSNT54456.2022.9787667","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787667","url":null,"abstract":"NFT is an abbreviation for non-fungible token, which indicates it cannot be replaced or interchanged due to its unique features. It is just a digital asset which symbolizes online collectibles such as art, music, and games and is protected by an authentic certificate generated by the block-chain technology that underpins cryptocurrency. The most important use of NFTs nowadays is in digital material. NFTs boost content producers' revenues by powering a creator economy in which artists cede ownership of their work to the networks they use to advertise it. Keeping in mind we have developed a system where one can mint the desired artwork directly from the web app which is automatically added to his OpenSea marketplace with his metamask wallet address which he will be use to create the account on OpenSea. The artwork will spontaneously be visible in my collection section of OpenSea from where the person can do many things including the change in the price of Artwork (NFT) he owns and release it on sale or take it out for auction. Also, details like elements of the artwork and contract address are also available which provides access to view all the activities performed by that particular NFT.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134056633","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}
Md. Ramish, Anurag Sinha, Jay R. Desai, Aditya Raj, Yuvraj Singh Rajawat, Piyush Punia
{"title":"IT Attack Detection and Classification using Users Event Log Feature And Behavior Analytics through Fourier EEG Signal","authors":"Md. Ramish, Anurag Sinha, Jay R. Desai, Aditya Raj, Yuvraj Singh Rajawat, Piyush Punia","doi":"10.1109/CSNT54456.2022.9787637","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787637","url":null,"abstract":"As the documentary action of every single enterprise and government agencies are being digitalized and several industries are heading towards complete Migration towards virtualization the risk of security threat, malicious attacks, criminal mindset are arising. Deep learning and AI have always been setting a new paradigm in one step above detection and classification of several attacks based on its file and features. Several enterprises utilize the historic data of their employees for storing cookies and understanding business processes. In this paper, we are proposing a new framework in which Malicious attacks can be classified using anomaly detection based on event users' log similarities and summaries of operations performed virtually. Also, the Classification of these relevant features log using Decomposed EEG signal is shown for detecting behavior more precisely using Kruskal- Wallis algorithm has been employed to select explicit static features. These selected features are used to classify the given EEG dataset into different categories using a supervised EEG decomposition algorithm.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132735956","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}
{"title":"Impact of Network Heterogeneity on Epidemic Mitigation Strategies","authors":"Jagtap Kalyani Devendra, Kundan Kandhway","doi":"10.1109/CSNT54456.2022.9787646","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787646","url":null,"abstract":"We formulate an optimal control problem to find best vaccination and treatment policies to minimize the impact of an epidemic on the population. Epidemic spread on heterogeneous human contact networks is modeled using the degree based compartmental model for susceptible-infected-recovered epidemic. Our formulation allows us to study the impact of varying network heterogeneity on the mitigation strategies. Network heterogeneity is varied by using different degree distributions for the network, such as, power law, power law with exponential cut-off, and Poisson. Network heterogeneity is a proxy for social distancing measures applied on the population—as restrictions tightens, high degree hubs disappear, thus, the nature of degree distribution changes from power law to Poisson. We find that high degree nodes assume less importance in mitigating epidemics as the network heterogeneity decreases. Also, epidemics are easier to control with decrease in network heterogeneity.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117273172","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}
Harshit.Bhatnagar, S. Patil, Aditya Kumar Gupta, Akshay Kumar, Abhay Sharma
{"title":"High Gain (1x4) Compact Arrow Shaped Patch Antenna Array Using Quarter Wave Transformer for 5G mm Wave Applications","authors":"Harshit.Bhatnagar, S. Patil, Aditya Kumar Gupta, Akshay Kumar, Abhay Sharma","doi":"10.1109/CSNT54456.2022.9787653","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787653","url":null,"abstract":"This research proposes a (1×4) compact patch antenna array that will operate in the 5G millimeter wave range between 44 to 50 GHz, proposed antenna array operates at 6 GHz, which is a quite large frequency range (impedance bandwidth). The patch has hybrid geometry two rectangular patches and two triangular patches were used and placed on FR4 epoxy substrate with a relative dielectric constant of 4.30 and can be used in a variety of applications. The suggested antenna has a total size of 30 mm x 14 mm and a height of 0.8 mm. High Frequency Structure Simulator (HFSS) was used to simulate the return loss & S11, (VSWR), impedance discrepancy and antenna gain of the suggested antenna.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114591460","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}
{"title":"Application of Machine Learning for Sentiment Analysis of Movies Using IMDB Rating","authors":"S. Rathor, Yuvraj Prakash","doi":"10.1109/CSNT54456.2022.9787663","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787663","url":null,"abstract":"In today’s environment, the customer behavior related to the product is important. The rapid growth of social media has made it easier to collect information about our products. Billions of customers share information about their products on social media pages. Manually managing large amounts of social media information is difficult. However, we have proposed a framework for analyzing customer sentiment using data mining and machine learning algorithms. The proposed framework consists of several steps to processes the information and try to find the good accuracy of the classification. The proposed framework is used for sentiment analysis of movie using IMDB rating. In this paper, the data preprocessing and feature extraction are done using data mining techniques. The result analysis shows that the proposed framework can be useful for better decision-making.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123567669","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}
{"title":"Enhancing the Performance of Hash Function Using Autonomous Initial Value Proposed Secure Hash Algorithm 256","authors":"B. Ambedkar, P. Bharti, Akhtar Husain","doi":"10.1109/CSNT54456.2022.9787561","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787561","url":null,"abstract":"To verify the integrity and confidentiality of data communicated through the web is a very big issue worldwide because every person wants very fast computing and secure electronic data communication via the web. The authentication of electronic data is done by hashing algorithms. Presently researchers are using one-time padding to convert variable-length input messages into a block of fixed length and also using constant initial values that are constant for any input message. So this reason we are proposing the autonomous initial value proposed secure hash algorithm-256 (AIVPSHA256) and we are enhancing the performance of the hash function by designing and compuiting its experimental results in python 3.9.5 programming language.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123837947","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}
Avinash Kumar, Ashish Rajanand, Anurag Deep Kujur, Y. Rathore, R. Janghel
{"title":"Segmentation of Rice Seedling using Deep Learning Algorithm","authors":"Avinash Kumar, Ashish Rajanand, Anurag Deep Kujur, Y. Rathore, R. Janghel","doi":"10.1109/CSNT54456.2022.9787601","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787601","url":null,"abstract":"The objective of deep learning is used to recognise crops and weeds on the farm. It can be also termed as smart farming. To reduce the pollution caused by spraying excess fertilizer and herbicide in the rice crops, it becomes necessary to correctly locate the rice seedling and weed. Rice seedling Segmentation remains a difficult process. In this paper, we propose a method called semantic segmentation using FCN, Unet, Fast-SCNN, SegNet to differentiate weed from crops. The average accuracy of SegNet is 92.08% and using Unet is 87.5% which is an evolved model of CNN. We have illustrated different algorithms for this process but the main architecture is SegNet which has shown best accuracy among them.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124588158","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}
{"title":"Face Mask Detection Analysis for Covid19 Using CNN and Deep Learning","authors":"Dinesh Sharma, G. Tomar","doi":"10.1109/CSNT54456.2022.9787579","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787579","url":null,"abstract":"The planet was severely affected by Coronavirus Disease 2019. The wearing of masks in public places is a big way of protecting people. In addition, many providers of public service only require consumers to wear masks correctly. However, only a few studies are focused on image analysis on face mask detection. I propose in this paper, a high-precision and effective mask detector for Mask Detection Method. Recognition from faces is a popular and significant technology in recent years. Face alterations and the presence of different masks make it too much challenging. In the real-world, when a person is uncooperative with the systems such as in video surveillance then masking is further common scenarios. For these masks, current face recognition performance degrades. An abundant number of researches work has been performed for recognizing faces under different conditions like changing pose or illumination, degraded images, etc. Still, difficulties created by masks are usually disregarded. The primary concern to this work is about facial masks, and especially to enhance the recognition accuracy of different masked faces. A feasible approach has been proposed that consists of first detecting the facial regions. So, n orders to detect whether you are wearing a face mask to protect yourself, I decided to construct a simple and basic Convolutional Neural Network model, using TensorFlow and Keras library. With the prevailing pandemic of COVID-19, these systems will benefit many kinds of organizations worldwide. These types of systems are especially important.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125478321","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}
{"title":"Offline Handwritten Text Recognition Using Hybrid CNN–BLSTM Network","authors":"R. Namdeo, Chetan Gupta, Ritu Shrivastava","doi":"10.1109/CSNT54456.2022.9787587","DOIUrl":"https://doi.org/10.1109/CSNT54456.2022.9787587","url":null,"abstract":"Handwriting text recognition, or htr, is a computer capability to receive and understand handwritten data from various sources, like paper journals and graphics, touchpad screen. Identification of handwritten text is a new and complicated field of study that has a vast range of applications in banks and other enterprises. In this work , we use a hybrid convolutional neural network (CNN) and Hybrid Bi-directional Long Short Term Memory (BLSTM) based Recurrent Neural Network design to determine text. We deploy CNN layers to create a variety of activation maps. Activation maps highlight the image's most important characteristics. This feature is then feed to BLSTM layer for encoding and decoding visual feature present in the input image .Our CNN-BLSTM based implementation is experimented with the dataset IAM to obtain the accuracy of handwritten text. We achieve an accuracy of 97.8% in IAM word dataset.","PeriodicalId":398594,"journal":{"name":"2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128612000","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}