2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)最新文献_第6页

Analysis of Frequency Selective Surface With Quadruple Jerusalem Cross Unit Cell for WLAN Applications 无线局域网中四倍耶路撒冷交叉单元的频率选择面分析

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157800

Saranya Madheswaran, R. Venkatesan

引用次数: 0

Predicting autism in children at an early stage using eye tracking 用眼动追踪技术预测儿童早期自闭症

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157663

R. M. Kannan, R. Sasikala

{"title":"Predicting autism in children at an early stage using eye tracking","authors":"R. M. Kannan, R. Sasikala","doi":"10.1109/ViTECoN58111.2023.10157663","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157663","url":null,"abstract":"Autism spectrum disorder (ASD) refers to a collection of conditions characterized by challenges in areas such as social interactions, communication, and repetitive behavior. Children with autism spectrum disorders often experience difficulties in processing and responding to social cues, which can lead to deficits in social skills and nonverbal communication. Children with ASD have been observed to have problems in maintaining eye contact. The main aim of this study is to use the eye tracking scan path images as a biological indicator to identify children with autism. The dataset used in this study has 547 visualized scanpath images collected from 59 children. The aim of this study is to utilize these scanpath images and formulate an autism diagnosis technique with the help of machine learning algorithms. The proposed model extracts the trainable features from the images and it is fed to a logistic regression classifier and a multi-layer perceptron classifier (MLP). A comparative study between the performance of the proposed model and a custom convolutional neural network is also presented.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116231362","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

Ergodic Capacity of Mixture Gamma and Double Generalized Gamma Distribution in Dual Hop RF/FSO Transmission System 双跳RF/FSO传输系统中混合伽玛和双广义伽玛分布的遍历容量

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157813

P. Jain, N. Javanthi, M. Lakshmanan

引用次数: 0

CONGEST: An Algorithm to Detect Congestion Zones Based on Unmanned Aerial Vehicle (UAV) Flight plans CONGEST:基于无人机飞行计划的拥堵区域检测算法

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157846

Shashank Parmar, Rahul, Shashank Taneja

{"title":"CONGEST: An Algorithm to Detect Congestion Zones Based on Unmanned Aerial Vehicle (UAV) Flight plans","authors":"Shashank Parmar, Rahul, Shashank Taneja","doi":"10.1109/ViTECoN58111.2023.10157846","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157846","url":null,"abstract":"One of the primary problems in the Unmanned Aerial System (UAS) field is the potential increase in conflicts and congestion as the UAS gets incorporated into traditional manned airspace. Our research work aimed to come up with an innovative idea to identify potential congestion zones based on the UAV flight plans. A flight plan is a planned route for a flight that contains a set waypoint defined by latitudes, longitudes, and altitudes. Congestion is defined as a circle of radius ‘R’ that has more than a given number of crossings. Conventional clustering algorithms such as DBSCAN, K-means, K-medoids, CLIQUE, etc are designed for static points/objects i.e., the features of the objects remain constant. However, in the case of Unmanned Aerial Vehicles (UAVs), the UAVs keep on changing their position from time to time. Hence, conventional clustering algorithms cannot be applied to the given problem. We have proposed a heuristic algorithm named CONGEST, based on the DBSCAN Clustering algorithm. Our algorithm can identify 91.5-98.5% of the congestion zones in a span of a few seconds.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121569449","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

APD - ML: Air Pollution Detection Using Machine Learning Algorithms APD - ML:空气污染检测使用机器学习算法

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157131

A. Sofia, Shrinee Venisha J, S. K, Soundarya K, Theepiga M

{"title":"APD - ML: Air Pollution Detection Using Machine Learning Algorithms","authors":"A. Sofia, Shrinee Venisha J, S. K, Soundarya K, Theepiga M","doi":"10.1109/ViTECoN58111.2023.10157131","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157131","url":null,"abstract":"To analyze the air quality of any country, a machine learning technique is being developed and an air quality indicator is proposed for a particular area. Air Quality Index is considered to be a basic measure which can indicate the levels of SO2, NO2. etc. over a particular amount of time. We technologically put forward a model to determine the air quality index in view of historical data of preceding years and computing the same for the forthcoming year considering it as a gradient decent attached boosted multivariable regression problem. We enhance the proposed model's effectiveness by relating cost estimation on behalf of the problem to be a predictive one. Thus this proposed system resolve successfully and work well to envisage the air quality indicator of any entire country or state or any bounded region furnished with enough historical data about contaminants in air. In the proposed model, subsequently machine learning technique is assimilated, upright enactment with performance is accomplished further than the standard regression model. The implementation of envisaging air quality index is prepared for our country India as well as accurateness of 96% is attained via XG Boost Algorithm joined with LightBGM algorithm to find an accurate solution that is in adjacent proximity to the ideal solution.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125114454","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

Chronic Kidney Disease Detection Using Machine Learning Approach 使用机器学习方法检测慢性肾脏疾病

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157496

K. Pujitha, N. Soni, Lepakshi Fariha Eram, Pullaganti Nikhitha Sai, Segu Divija, Reddicherla Sai Supriya

{"title":"Chronic Kidney Disease Detection Using Machine Learning Approach","authors":"K. Pujitha, N. Soni, Lepakshi Fariha Eram, Pullaganti Nikhitha Sai, Segu Divija, Reddicherla Sai Supriya","doi":"10.1109/ViTECoN58111.2023.10157496","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157496","url":null,"abstract":"Chronic kidney disease is a critical and dangerous medical condition that can lead to many problems if it is not treated properly or detected at an early stage. It is a medical condition that can also lead to kidney failure. The waste and extra fluids present in the blood are removed by the kidneys and then passed from body through urine. The body may accumulate hazardous amounts of electrolytes, fluids, and waste if you reach the last stages of chronic renal disease. Because kidney failure does not initially manifest any symptoms, the beginning date may not be identified, and the patient's sickness may not even be recognized. We must identify the patients with chronic kidney disease early so that treatment can begin in order to prevent or slower the advancement of the disease and prevent the emergence of other related issues. To overcome this situation, we have developed a system to detect the disease using preprocessing of data, feature selection, and machine learning algorithms for which Logistic Regression, Extreme Gradient Boosting, Random Forest, Support Vector Machine, Decision Tree, and Naive Bayes are used. The accuracy of these algorithms is analyzed and compared to predict the disease precisely. The algorithm which has provided the best results is implemented for the disease prediction. We have enhanced the performance and effectiveness of the model by removing unnecessary attributes from the dataset and only gathering those that are most beneficial.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131568509","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

Congestion Management: Using Deep transfer learning for Traffic Classification, Layer4 forwarding, OpenFlow meter 拥塞管理:使用深度迁移学习进行流量分类，Layer4转发，OpenFlow meter

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157854

Subhasish Ghosh

{"title":"Congestion Management: Using Deep transfer learning for Traffic Classification, Layer4 forwarding, OpenFlow meter","authors":"Subhasish Ghosh","doi":"10.1109/ViTECoN58111.2023.10157854","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157854","url":null,"abstract":"Network traffic classification methods are used for congestion management, QoS delivery, billing in ISPs, and security purposes in firewalls. In the past, port-based, data packet inspection, and traditional machine learning techniques have all been widely utilized. However, their accuracy has decreased as a result of the Internet traffic's tremendous changes. The training data and test data are assumed to have independent, identical distributions by deep learning models used for network traffic classification. Due to changes in traffic features, this assumption could be incorrect in actual traffic classification. The classification of new network traffic will fail to use the models that were trained on the existing data. In this research, a deep transfer learning model without the aforementioned assumption is provided. The deep transfer learning technique is used to transfer the knowledge learned by the pre-trained traffic classification model to another model that has a smaller dataset and computational resources. The transfer learning model is built on ConvlD and BiGRU hybrid models that can achieve 98% accuracy in a completely new traffic classification target domain. In this research, deep transfer learning techniques are used to get over resource constraints and construct models for classifying network traffic based on deep learning. After classifying, the packets are forwarded by the OpenFlow switches according to the flow table configuration. Also, packets are forwarded by using Layer4 forwarding and OpenFlow metering methods for optimal bandwidth allocation to avoid network traffic congestion.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131590618","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

Bus Pass Multi Authority Approval System Using Logistic Regression 基于Logistic回归的公交通行多权限审批系统

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157180

E. G, Swetha. R, P. S, Shankari. G, Sharmitha. S, Shuji. J

{"title":"Bus Pass Multi Authority Approval System Using Logistic Regression","authors":"E. G, Swetha. R, P. S, Shankari. G, Sharmitha. S, Shuji. J","doi":"10.1109/ViTECoN58111.2023.10157180","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157180","url":null,"abstract":"This paper's main audience is individuals who are struggling to obtain a bus pass manually at the moment. They can obtain it in this project with the aid of an E-platform. Users must register their information. After viewing their information, the Administrator will be able to approve the bus pass. The bus pass will then be produced. Users can examine information by logging in with their special IDs and obtaining a bus pass. They can renew the bus pass if it expires. With the aid of UPI, they can make the payment. The utilization of AI to develop an E-transport pass framework is an innovative methodology that utilizes state-of-the-art innovation to improve the viability and productivity of the transport pass framework. There are various downsides to the regular transport pass framework, like the potential for extortion, botches in the manual information section, and the shortfall of constant information examination. The E-transport pass framework utilizes AI calculations to approve tickets consequently, upgrade information section precision, and recognize and stop false movement.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127767942","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

Optimizing Okra Plant Disease Management with Image Analysis and Deep Learning 利用图像分析和深度学习优化秋葵植物病害管理

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10157448

Kshitiz Kumar Singh, Divyanshu Tirkey, Anand Harsh, S. Tripathi, Smitha Kurup, B. Char

{"title":"Optimizing Okra Plant Disease Management with Image Analysis and Deep Learning","authors":"Kshitiz Kumar Singh, Divyanshu Tirkey, Anand Harsh, S. Tripathi, Smitha Kurup, B. Char","doi":"10.1109/ViTECoN58111.2023.10157448","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10157448","url":null,"abstract":"Indian agriculture is a significant contributor to the nation's economy. The identification of agricultural diseases is a critical field of research nowadays. One of the issues that leads to a decline in crop quality and productivity is this one. To treat Okra plant disease as effectively as possible, this study explores the use of image analysis and deep learning approaches. Okra is a crucial crop for food security, but it is frequently afflicted by several diseases that can drastically lower crop output and quality. To treat Okra plant disease as effectively as possible, this paper discusses image analysis and deep learning approaches. The inspection in conventional disease control techniques can be time-consuming and prone to human mistakes. This article suggests a unique method for automatically identifying and diagnosing diseases in okra plants using deep learning algorithms and image analysis. A convolutional neural network (CNN), ResNet152v3, and Inceptionv3. Cropped photos of leaves are used in this instance, and after processing them, it will determine whether or not the crop is affected by the disease. If a condition is found, the sort of disease it is and possible treatments, such as chemicals or pesticides, are provided. The productivity and economic process will both rise.","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133220869","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

Cloud and AI Powered MediTrack Application For Elderly and Visually Challenged Person 云和人工智能驱动的MediTrack应用程序，用于老年人和视障人士

2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN) Pub Date : 2023-05-05 DOI: 10.1109/ViTECoN58111.2023.10156918

Sriviveknath S R, Vijay A, S. V., Poonkuzhali S

{"title":"Cloud and AI Powered MediTrack Application For Elderly and Visually Challenged Person","authors":"Sriviveknath S R, Vijay A, S. V., Poonkuzhali S","doi":"10.1109/ViTECoN58111.2023.10156918","DOIUrl":"https://doi.org/10.1109/ViTECoN58111.2023.10156918","url":null,"abstract":"The increase in illnesses and pandemics has forced doctors to care for patients nonstop, around-the-clock. Despite the fact that many people have used medical applications, none of them offer the full range of services that customers anticipate. This works seeks to helps elderly and visually challenged folks to consult the health practitioner at their convenience. Patients can obtain their medical history and prescriptions by connecting to doctors using the unique Id assigned to each user. We assist elderly and visually impaired persons in making appointments online so they can avoid waiting in huge lines at the hospital. For some reason the doctor couldn't make up with the scheduled appointment and this is where doctor suggestion system comes into picture where we analyze patient's past visits and recommend new appointments with doctors. Doctors can prescribe medicines to patients using the centralized prescription system which is stored using Firebase cloud Realtime Database, and with the Smart reminder, the patient is made sure to consume medicines at the prescribed time. Each and every patient has an electronic record (ER) maintained and stored in the cloud storage which makes sure to record the patient's history when visiting one or more doctors. The application has a center picture for the elderly persons, by the use of Voice assistant to perform necessary actions on the application and use almost all of the elementary functions. When a doctor is prescribing medicine to the patient, Our Smart Drug Interactor (SDI) gives a note suggesting the after-effects when the prescribed medicine is consumed along with other prescribed medicine using the Deep Neural Network","PeriodicalId":407488,"journal":{"name":"2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133522847","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