2023 International Conference on Networking and Communications (ICNWC)最新文献

{"title":"A Logical Investigation of Stock Market Prediction and Analysis using Supervised Machine Learning Algorithm","authors":"R. Dhanalakshmi, V. V. Kumar, Saleem Basha, N. Vijayaraghavan","doi":"10.1109/ICNWC57852.2023.10127391","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127391","url":null,"abstract":"In the Field of computer science, artificial intelligence (AI) is a broad field, which is concerned with structuring smart products and machines able to perform tasks which require the intellectual capability of humans. Artificial Intelligence is in need for Stock trading’s future. Robotic advisers examine millions of pieces of data using artificial intelligence and carry out the analysis at the best possible price. Market forecasts are more precise and effective thanks to the analysts. For providing higher returns, the trading firms efficiently mitigate the risk using Artificial Intelligence Techniques. Our proposed Stock Market system is a Web Application which uses the Random Forest Algorithm. The Random Forest Algorithm comes under Supervised Learning. With the system, one can forecast the stock prices for the subsequent days.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128467897","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":"Identification and Labeling of Textual Cyberbullying using BiLSTM and BERT","authors":"Shikhar S Gupta, Unnati Vadgama, T. R. Vedhavathy","doi":"10.1109/ICNWC57852.2023.10127308","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127308","url":null,"abstract":"In this aeon of digitalization, people are inclining more and more towards technology. This has both positive and negative aspects, and one of the negative effects is cyberbullying. Cyberbullying allows people to comment negatively on various social media platforms, this project aims at detecting and classifying such text. Using BiLSTM (Bidirectional Long Shortterm Memory) and BERT(Bidirectional Encoder Representations from Transformers), the cyberbullying text on various social media platforms is identified and classified into classes such as religion, age, gender, ethnicity, not_cyberbullying and other_cyberbullying. This helps in keep the record of types of cyberbullying that occurs on social media and whether it’s reduced over time after reporting it and taking strict measures against it.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115909576","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":"Image Classification with Deep Learning Methods for Detecting and Staging Bone Cancer from MRI","authors":"E. Lingappa, L. Parvathy","doi":"10.1109/ICNWC57852.2023.10127368","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127368","url":null,"abstract":"Mutations in cancer-causing genes can be passed down from parents to offspring. or because of DNA dam age from unprotected exposures to the elements. Cancer, which is brought on by unchecked cell development, can be lethal. Bone cancer begins when normally functioning bone cells undergo a malignant transformation and proliferate out of control, resulting in a tumour. When it comes to cancers of the bones, the incidence and severity rank high. To treat bone cancer effectively, early diagnosis and staging are essential. This study utilized CT and MRI with a Convolutional Neural Network to detect bone malignancy. The accuracy of the suggested technique was evaluated using 100 bone MRIs from patients who had already been validated. In this analysis, CNNs are utilised to determine if a bone tumour is benign or malignant. Classifying bone cancer using the proposed method is highly accurate (93.75 percent).","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123951512","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":"Candlestick Chart Based Stock Analysis System using Ensemble Learning","authors":"Angel Ann Varghese, J. Krishnadas, R. S. Kumar","doi":"10.1109/ICNWC57852.2023.10127261","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127261","url":null,"abstract":"The 1$8^{mathrm{t}mathrm{h}}-$century candlestick charts, which were first utilized in the Japanese rice market, are now frequently used in trading tactics across all financial markets. Candlestick charts make it possible to comprehend an asset’s opening, high, low, and closing values all in one image. In addition to these benefits, the abundance of candlestick chart patterns makes practical application challenging. A software framework that employs candlestick charts to forecast trend direction was built for this study. There are four stages of the project. A system that can identify candle patterns is developed in the first stage. The second stage involves executing training and testing procedures on data sets with labeled candlestick chart types and trend directions in order to assess the model’s performance. During the machine learning phase, open-source techniques like xgboost were applied. In the project’s final stage, it was discovered that the strategy focused solely on identifying candlestick patterns and taking positions in line with the trend based on the suggested methodology produced larger profits in 11 global indices than the Buy & Hold strategy. In comparison to the current accuracy of 53.8%, the model’s average forecast accuracy is 59.42%","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116680720","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":"A novel hybrid automatic intrusion detection system using machine learning technique for anomalous detection based on traffic prediction","authors":"D. Vinod, M. Prasad","doi":"10.1109/ICNWC57852.2023.10127442","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127442","url":null,"abstract":"Traffic classification is an automated technique that divides computer network traffic into several categories depending on different factors like protocol or port number. In a complicated context, traffic categorization is an important tool for network and system security. A monitoring system called intrusion detection looks for abnormal activity and sends out notifications. In order to safeguard a system from network-based attacks, Network Intrusion Detection Systems (NIDS) play a crucial role in monitoring and analyzing network traffic. Active and passive intrusion detection systems (IDS), network intrusion detection systems (NIDS), host intrusion detection systems (HIDS), knowledge-based (signature-based) IDS, and behaviorbased (anomaly-based) IDS are some of the numerous types of intrusion detection systems (IDS). Passive IDS is just designed to monitor and analyze network traffic behaviour and notify an operator of potential vulnerabilities and attacks, whereas Active IDS is also known as Intrusion Detection and Prevention System. A network’s malicious traffic is identified using a network-based intrusion detection system (NIDS). A host-based IDS monitors system activity and seeks for indications of abnormal behaviour. For networks with unidentified traffic, the intrusion detection system designed using flow and payload statistical characteristics and clustering approach needs additional clusters. The present intrusion detection system however is affected by false alarm rate, poor detection rate, imbalanced datasets and response time which lead to misclassification of intrusions in various scenarios. Hence, there is a requirement for developing an automated intrusion detection system that works well in different scenarios. The proposed system uses supervised and unsupervised intrusion detection and classification methods to increase the classification accuracy. To categorize the intrusions, dimensionality reduction strategies are used in conjunction with the classification procedure of logistic regression. Performance of intrusion detection system using PCA as dimensionality reduction algorithm has been evaluated with different classifiers such as Logistic Regression (LR), K-Nearest Neighbors (K-NN), Random Forest (RF), Support Vector Machine (Kernel SVM), Decision Tree (DT) using CIC IDS 2022 dataset. An automated way to detect intrusions has been proposed with cluster formation using adaptive weight butterfly optimization algorithm.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114944154","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":"Know Them: Convolutional Neural Networks For Facial Emotion Recognition","authors":"S. Swathi, M. B. Deepika Lakshmi, B. S. Minu Dhakshina, S. Aanandhini","doi":"10.1109/ICNWC57852.2023.10127451","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127451","url":null,"abstract":"Humans are capable of thousands of facial actions during communication that varies in complexity, intensity, and meaning. Emotions play a major role in Human life. Visually challenged is one of the marginalized people who face day-to-day problems without seeing the world. They find it difficult to predict the emotional state of a person surrounding them, this project helps them to understand the emotions of others through the facial expressions and thus interact well with people socially especially in public places. The rapid advancement in technology has now helped visually challenged people to explore the world through mobile phones. Few features that help them use these devices are virtual assistants, text-to-voice converters, image recognizers etc. Know Them is an application that uses image processing methods and Convolutional Neural Network (CNN) algorithms to identify the emotions of the people that the visually challenged wanted to know.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451126","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":"Telemetry Simulation & Analysis","authors":"Pratyusha Gupta, Harshal Gupta, S. Ushasukhanya, E. Vijayaragavan","doi":"10.1109/ICNWC57852.2023.10127430","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127430","url":null,"abstract":"The purpose of this project is to analyze telemetry data for a comprehensive analysis of driving conditions, range, electric motor performance, and other characteristics linked to telemetry packets based on information transmitted by the car Telematics Control Unit (TCU). The strategy is intended to assist us in eliminating the requirement for sending test vehicles out to verify every tiny modification made by the software team and its impact on the core functionality of the vehicle systems. In the automobile industry, telemetry provides very useful information about a driver’s performance and vehicle by collecting telemetry data from sensors within the vehicle TCU. This is done for various reasons varying from, insurance rating and predictive maintenance to staff compliance monitoring. Telemetry analysis has taken over the complete control of the automobile sector. These conclusions are driving the automobile industry toward some unbelievable and never-before results. The automobile industry is on a roll and Telemetry Analysis is its wheels. Telemetry Analysis has helped the automobile industry achieve things that were beyond our imaginations from analyzing the trends to understanding the supply chain management, from taking care of its customers to turning our wildest dream of connected cars into a reality, Vehicle Telemetry Analysis is well and truly driving the automobile industry crazy.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125383004","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":"Academic Information Storage and Verification Using Blockchain Technologies","authors":"S. Prabu, M. Sumathi, M. Rajkamal","doi":"10.1109/ICNWC57852.2023.10127235","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127235","url":null,"abstract":"In general, academic verification of an employee is done manually takes a lot of time, cost and less trustworthy. The trustworthiness of the certificate is dependent on the employee. Due to financial benefits and other advantages, fake certificates are easily created by fraudulent members. Detecting a fraudulent certificate is a hard process. Nowadays, blockchain technology provides wonderful benefits to all sectors for maintaining documents in an immutable manner. Once the data is stored in a blockchain, no one can change or delete that data. Hence, blockchain technology is used to store and verify academic information is highly scalable and guaranteeing the privacy of users’ data. In a proposed work, the blockchain network is created between the educational institutions and employers for efficient information sharing and verification. For unique identification of the certificates QRcode is assigned to each academic certificate. By using SHA256 algorithm the hash value of the QRcode is calculated and has been stored in a block in a distributed ledger. The employer calculates the hash value of the certificate which is submitted by the employee and compared this hash value to the hash value of the certificate stored in the block. If both are equal, the employer identifies it’s a valid certificate or else rejected it’s invalid certificate. Thus, trustworthy verification like confidentiality, authentication, authorization, ownership and privacy is achieved through blockchain technology. Likewise, the certificate verification latency is reduced and throughput is increased in this approach.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128714347","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":"Study and analysis of various COVID-19 prediction techniques using CT images: A challenging overview","authors":"Sonali Dhamele, G. Niranjana","doi":"10.1109/ICNWC57852.2023.10127326","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127326","url":null,"abstract":"coronavirus disease (COVID-19) has scattering quickly across a globe due to its exceedingly infectious natural world and is affirmed as epidemic by World Health organization (WHO). This deadly disease has depicts the globe to a standstill. From a breakdown economy to increasing bereavement charges, this viral disease is infectingeverybody. It is significant to hold the increase to diminish the danger of affection. This can be carried outby means of extensive testing and tracing of contacts. In the detection of COVID-19, three major screening processes are utilized, which include chest X-Ray (CXR), Computed Tomography (CT) as well as Reverse TranscriptasePolymerase Chain Reaction (RT-PCR). To struggle against a rapid increase of coronavirus, analysis of CT clinical images engage a vital part in precise diagnostic. Hence, this survey paper overviews some techniques consequent to a detection of COVID-19 utilizing CT images. This survey assess 25 research papers concentrated on COVID-19 prediction utilizing CT images and presented method-wise overviews, like deep learning-based techniques, optimization based methods, transfer learning based techniques, and machine learning based approaches. An evaluation takes part in a review based on cataloging probe techniques, tools etemployed datasets, publication year, and evaluation metrics for the prediction of COVID-19. At last, the troubles and demerits of reviewed methods are explicated, which motive probers for introducing new effective methods for predicting COVID-19 by wielding images of CT.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122488253","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":"Optimized Crop Cultivation Based on Weather Monitoring System","authors":"Anubhav Mishra, Merin Sheejith, B. Yamini","doi":"10.1109/ICNWC57852.2023.10127317","DOIUrl":"https://doi.org/10.1109/ICNWC57852.2023.10127317","url":null,"abstract":"This project furnishes an automated vision of a climate and plant monitoring system. Based on it, the device stores data which are collected at a predetermined sampling interval for monitoring and analysis of various environmental parameters such as humidity, temperature, barometric pressure, wind speed and direction, air quality, rainfall amount and location coordinates. The device’s central processing unit consists of an Arduino UNO that is used in collecting data and information about various sensors and probes. This type of system can be deployed in controlled environments such as farms and aquaculture. The idea behind this is primarily to monitor and forecast the weather at a micro-ecological level, and monitor premeditated situations to issue warnings in adverse circumstances. Hardware-wise, it consists of a programmable circuit board and for software an integrated development environment that functions on available operating systems is used. Arduino’s microcontroller is used to develop a weather monitoring system based on temperature and humidity variables obtained from a DHT11 sensor. When testing, the monitoring system should be able to convey whether the weather is harsh, normal, or rainy, etc. based on accurate temperature and relative humidity within a 20-meter range. This project primarily incorporates the field-based control systems of two studies and the data collection strategy to produce a database system based on the attributes used to generate the data presented. The main elements here have been selected based on the sensors that are commonly used to build the system to design an effective weather monitoring project. The recommended sensors are used here to measure and collect temperature and humidity data. Weather monitoring proposes a system that monitors the weather in real-time through a mobile application. This very underrated platform to connect all these different types of sensors and broadcast their data over the internet is provided by Arduino UNO. The main intention of the work is to record the weather, which can be easily monitored remotely via the Internet of Things with the help of Arduino UNO. This lays out users with an easier, more reliable, and quicker way to assess the weather and other environmental parameters.","PeriodicalId":197525,"journal":{"name":"2023 International Conference on Networking and Communications (ICNWC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126324166","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}