2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)最新文献_第5页

Design and Implementation of Virtual Tour Guide App 虚拟导游App的设计与实现

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9752804

Baivab Maulik, Aditi Nayak, S. U., Simmi Alok, D. N

引用次数: 1

Design and analysis of sickel shape patch antenna with flexible non-woven material for IoT applications 物联网应用中柔性无纺布材料镰刀形贴片天线的设计与分析

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753176

Brenda M, L. F. Telfer, Soubhik Mandal, Tedabariki Vijay, Joy Kumar Saha

引用次数: 0

IoT Based Health Observance System using Fog Computing: A Precise Review 使用雾计算的基于物联网的健康监测系统:精确回顾

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753198

T.M.Saravanan, T. Kavitha, S. Hemalatha, M. Ajmal

引用次数: 0

Deep Learning and Machine Learning Based Efficient Framework for Image Based Plant Disease Classification and Detection 基于深度学习和机器学习的植物病害图像分类检测高效框架

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753623

P. Nancy, Harikumar Pallathadka, M. Naved, K. Kaliyaperumal, K. Arumugam, Vipul Garchar

{"title":"Deep Learning and Machine Learning Based Efficient Framework for Image Based Plant Disease Classification and Detection","authors":"P. Nancy, Harikumar Pallathadka, M. Naved, K. Kaliyaperumal, K. Arumugam, Vipul Garchar","doi":"10.1109/ICACTA54488.2022.9753623","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753623","url":null,"abstract":"Without agriculture, human existence would be inconceivable. A large percentage of the world's population relies on agriculture for their daily needs. In addition, it creates a big number of jobs in the area. Using traditional agricultural practices results in lower yields, which is the fault of farmers. Agriculture and allied sectors will continue to be critical to the economy's long-term growth and prosperity. Farming has a slew of challenges, including disease detection and control and crop monitoring and tracking. Farming with intelligence is a realistic option in many situations. Smart agriculture is now possible because to the internet of things and machine learning approaches. Computer vision, image processing, and machine learning techniques are used in the automated leaf disease diagnostic system to analyze photographs of diseased leaves. A farmer can make an educated choice regarding a plant illness thanks to automated disease detection equipment that speeds up the diagnostic process. A farmer had to first send the contaminated leaf to a pathology lab for confirmation of the illness, which was a tedious process. It is the purpose of this paper to propose a framework for the real-time classification of agricultural images. Crop disease pictures categorization and illness prediction are made easier using this system.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122871704","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: 14

Performance Evaluation of Collision Avoidance in Last Slot Algorithm for IEEE 802.11 DCF IEEE 802.11 DCF中最后插槽避碰算法的性能评价

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753405

W. Srichavengsup, K. Kittipeerachon, Prawet Ueatrongchit, Sorawit Fongin

引用次数: 0

Electric Vehicle Speed Control with Traffic sign Detection using Deep Learning 基于深度学习的交通标志检测的电动汽车速度控制

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753624

Karthi S P, Ahash Ram R L, Buvanesh K K, Eric Amalan J, H. S.

{"title":"Electric Vehicle Speed Control with Traffic sign Detection using Deep Learning","authors":"Karthi S P, Ahash Ram R L, Buvanesh K K, Eric Amalan J, H. S.","doi":"10.1109/ICACTA54488.2022.9753624","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753624","url":null,"abstract":"The prime focus is mainly on e-Vehicles ADAS which will be a future mode of transportation. Road accidents are the major cause of death. The main issues that cause road accidents are ignorance of traffic rules and improper traffic rules following. Where traffic rules have two types traffic signboards and traffic signals. The proposed system, Traffic Sign Detection along with Electric Vehicle Speed Control using Deep Learning and CAN protocol will help assist the driver and reduce the road accidents caused by traffic rules ignorance. In this system, a camera is fixed in the vehicle windshield that captures the traffic signs on the roads. The camera sensor will send an image as a signal to ADAS/AD ECU through Ethernet wire where the captured image undergoes processing and is identified using the Deep Learning CNN technique in ADAS/AD ECU Microcontroller. Then, the ADAS/AD ECU tells the Transmission ECU to reduce the current speed to a specific speed and also to Cluster ECU to display an alert message to the driver in the cluster display using CAN protocol.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121667137","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: 2

Reading behind the tweets: A sentiment Clustering Approach 推文背后的阅读:情感聚类方法

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753107

Anshu Saxena, Vandana Bhagat, Jayant Mahajan

引用次数: 1

Soft Computing based Brain Tumor Categorization with Machine Learning Techniques 基于软计算的脑肿瘤分类与机器学习技术

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9752880

S. S, Sasipriya S, U. R

{"title":"Soft Computing based Brain Tumor Categorization with Machine Learning Techniques","authors":"S. S, Sasipriya S, U. R","doi":"10.1109/ICACTA54488.2022.9752880","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9752880","url":null,"abstract":"When it comes to medical science, radiology is a wide area that demands further information and thought in order to execute an appropriate tumour examination. This study makes use of MRI sequence pictures as input images to identify the tumour site, and as a consequence of this work, a malignant segment and detection technique is established. This expression is difficult to perform because of the considerable variability in the presence of cancer tissues linked with different inmates, as well as the similarity among normal tissues in the majority of cases, which makes the task difficult to finish. The most significant goal is to divide the brain into two groups: those with malignant tumours and those who do not have malignant tumours. There are four primary phases in the system that is presented. For efficient malignant detection, the registration process is carried out first using Edge based Contourlet Transformation, followed by segmentation of tumour points using region-expanding segmentation, followed by aspect extraction using two types of texture features, namely Otsu Thresholding, K-means, and Local Binary markings texture aspect, and finally, classification using neural network methods is imported out. Using reverse propagation detection of malignancy from a Slices scan image, the proposed approach is a one-of-a-kind procedure that may be used to identify the existence of tumours. For classification, a backpropagation method was utilised, and the accuracy of the classification was increased as a result. A variety of MRI sequences are used to test the proposed technique, which is implemented in Mat lab and yields experimental results for Image Registration and segmentation using point of growth. When the segmented photographs are compared to the victims' database, a method called Backpropagation neural network classification is used to classify them as serious or benign, respectively.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114821539","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: 6

Smart Phone based Microscopic Image Acquisition and Quantifying System for Detecting Dengue 基于智能手机的登革热显微图像采集与定量检测系统

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753482

Ramakrishna M M, V. Karthikeyan

{"title":"Smart Phone based Microscopic Image Acquisition and Quantifying System for Detecting Dengue","authors":"Ramakrishna M M, V. Karthikeyan","doi":"10.1109/ICACTA54488.2022.9753482","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753482","url":null,"abstract":"Mobile phones with high end configurations are now a found day-to-day use everywhere even in the rural side. At the same time, Healthcare sectors are extending their technological support to reach the villages to get benefits in spite of their geographical distance and connectivity with the urban facilities. It is necessary to rectify the problems in healthcare field particularly on the short resource areas by finding modern techniques. For microscopic imaging applications, researchers have created various unique devices that enable the high resolution picture taking, communication, and processing abilities of mobile phones. We believe that contemporary mobile phones with cameras larger than 8 Mega Pixels are capable of obtaining high-resolution images at a wide ways of amplifications useful for single-cell imaging. Automated focus of the camera, as well as color gain requirements, result in decreased image resolutions, lowering color capture accuracy. As a result, we devised a strategy for reducing such roadblocks to precise image quantification. These microscopic images taken from mobile phone can be very reliable and simple to get the quantitative microscopic images for various kinds of medical and scientific applications.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126767128","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

Manzil: An Interactive Data Visualization Project Exploring Everyday Spaces Manzil:一个探索日常空间的交互式数据可视化项目

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753082

Aman Aslam Aga, Raktim Raj Kalita, Harpreet Jaagi, R. Bachate, Kaashvi Garg

{"title":"Manzil: An Interactive Data Visualization Project Exploring Everyday Spaces","authors":"Aman Aslam Aga, Raktim Raj Kalita, Harpreet Jaagi, R. Bachate, Kaashvi Garg","doi":"10.1109/ICACTA54488.2022.9753082","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753082","url":null,"abstract":"This paper intricately documents every moment, that is from the point of realization for the creation to an Arduino-based situated display based on IoT and tangible interactions as a result of movement-based triggers. A classroom project turned pseudo-reality, through ethnomethodology it has been put on record the evolution of research by devoting attention to the observation of commonplaces that are more or less taken for granted in everybody's routines and how on a ride to enrich that experience the team landed on various abstractions that work on collectively producing pillars of social situations. From here on the paper will shape its way from an introduction about situated displays and why the study went ahead with it for their classroom project, to how a story was composed around the mentioned display. Later, an intricate discussion about the implementation, with regards to the Arduino, the permutation combination was put into figuring out the best channels to power the hardware required. Following that, the study focuses on ordinary methods that ordinary people use to analyze their response to a given stimulus. Exploring various variables to analyze positive and negative reactions and building onto a worthwhile experience during the span of a flight of stairs was the most intricately implemented part of the whole project which came right after. Project Manzil is way beyond a public display yet has a horizon to cross ahead in terms of data visualization, and this paper from here on chronicles the journey to reaching a full mount public/situated display for the college.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130436300","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