2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)最新文献_第3页

A Novel Salp Swarm Algorithm With Attention-Densenet Enabled Plant Leaf Disease Detection And Classification In Precision Agriculture 基于注意力密度的海藻群算法在精准农业中实现植物叶片病害检测与分类

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753001

S. Devi, A. Muthukumaravel

{"title":"A Novel Salp Swarm Algorithm With Attention-Densenet Enabled Plant Leaf Disease Detection And Classification In Precision Agriculture","authors":"S. Devi, A. Muthukumaravel","doi":"10.1109/ICACTA54488.2022.9753001","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753001","url":null,"abstract":"Recent technological advancements enable precision agriculture to improve crop productivity and quality. Since plant diseases mainly affect crop production and reduce profit, necessary tools are needed to detect plant diseases at an earlier stage. Automatic detection of plant diseases becomes essential to identify the occurrence of plant diseases and take remedial actions. The latest advancements of computer vision and artificial intelligence techniques can be used to design effective plant leaf disease detection models. This paper presents a novel salp swarm algorithm with attention-DenseNet enabled plant leaf disease detection and classification (SSADN-PLDDC) technique for precision agriculture. The major intention of the SSADN-PLDDC technique is to recognize the presence of plant leaf diseases using computer vision and image processing methods. The SSADN-PLDDC technique initially employs Gabor filtering to pre-process the input images. In addition, SSA with extreme learning machine (ELM) model is utilized as an image classification technique where the parametersinvolved in the ELM are optimally adjusted by using SSA. The experimental result analysis of the SSADN-PLDDC technique is validated using benchmark dataset and the experimental results reported the enhanced outcomes of the SSADN-PLDDC technique over the recent approaches.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"144 2 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":"133365957","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: 3

Wearable Sensors and Real-Time System for Detecting violence using Artificial Intelligence 使用人工智能检测暴力的可穿戴传感器和实时系统

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753223

B. Arthi, S. S, K. PoornaPushkala, Amit Arya, Dasari Rajasekhar

引用次数: 2

Development of Machine Learning Based Framework for Classification and Prediction of Students in Virtual Classroom Environment 基于机器学习的虚拟课堂环境下学生分类与预测框架的开发

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9752918

B. Loganathan, Indrajit Patra, Vipul Garchar, Harikumar Pallathadka, M. Naved, Sanjeev Gour

引用次数: 8

Hydroponic Nutrient Solution for Optimized Greenhouse with IOT 物联网优化温室水培营养液

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753346

Josephine Ruth Fenitha, S. Mirudhula, K. Subhashini, R. Sriharidha

{"title":"Hydroponic Nutrient Solution for Optimized Greenhouse with IOT","authors":"Josephine Ruth Fenitha, S. Mirudhula, K. Subhashini, R. Sriharidha","doi":"10.1109/ICACTA54488.2022.9753346","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753346","url":null,"abstract":"Looking at it in a large scale, Agriculture is always an integral part of our community. With an increasing trend of population growth, the food production also keeps increasing. With the focus currently changes to the trend of sustaining the environment, the possibility of growing plants anywhere with or without soil has gained great interest among the people in society. There are many negative impacts in the tradition and Conventional way of agriculture which has now been addressed by growing plants with the help of hydroponic methods instead. Water is used as the medium for growth in Hydroponic gardening systems instead of soil. It leads to achieve greater benefits like getting higher yields and efficient usage of water. It can also be designed to support production all through the year without a break. Without depending on the climatic conditions, setting up a self-sufficient hydroponic system allows the possibility of growing plants remotely, especially in areas where farming can be a very big challenge due to unseasonal climatic conditions. Also, it reduces the workload of people who look after plant maintenance. Earlier thesis papers related to this like a project called “Automated hydroponics greenhouse” in 2017 and “Automated Plant Holder for Compact Area” in 2018 was a source of inspiration for us to give a research on this project. In our research there are three goals. Primarily, it is required to find if it is possible to create an autonomous hydroponic system which is also relatively feasible with cost-efficient materials. Secondly, to verify whether plants can be accessed through remote mode and also to manage that system with less human interaction. Finally, how this kind of system would affect the efficiency of operating the system will be analyzed.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"34 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":"115771041","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

An Effective Decision Support System for Travel in COVID'19 Pandemic using Fuzzy Rules and Intelligent Algorithms 基于模糊规则和智能算法的COVID - 19大流行出行决策支持系统

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753273

S. G., Ishika Naik, Anika Jagati, Heetakshi Fating, P. M

{"title":"An Effective Decision Support System for Travel in COVID'19 Pandemic using Fuzzy Rules and Intelligent Algorithms","authors":"S. G., Ishika Naik, Anika Jagati, Heetakshi Fating, P. M","doi":"10.1109/ICACTA54488.2022.9753273","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753273","url":null,"abstract":"Travel is important for every human being and it impacts in all aspects of life ranging from personal to societal development. COVID'19 pandemic has changed the way we think to travel. Exploring the impact of the Covid-19 pandemic in the place the user needs to travel thereby facilitating user perception on travel is becoming a mandate nowadays. Travel perception is also important for variety of day-to-day activities like transportation of goods and services, health related travel etc., This work aims to create comprehensive and efficient prediction models, facilitated by a convenient user interface to predict how risky or convenient it is for a user to travel in a time where COVID-19 is prevalent. The predictions made are based on the location they wish to travel using various Machine Learning models. The results are combined with the individual's health history to arrive at an optimized decision. The model is trained using a comorbidities dataset as well as a location- wise weather dataset, which allows us to make the prediction of whether travelling is dangerous for the user or not. The user interface is designed to show predictions for various districts. The trained model is tested using the data provided in social media and government websites provided for prediction","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"78 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":"126075249","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

A Dynamic Resource Allocation Protocol: Device to Device Communication For MANETs 动态资源分配协议:用于manet的设备到设备通信

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753041

P. Sathyaraj, S. Rukmani Devi, A. Swethareddy, L. Manimegalai, K. Kannan, Babu M

引用次数: 0

Perceptred Feature Based Kriging Gradient Boost Classification for Big Data Driven Marine Weather Forecasting 基于感知特征的Kriging梯度提升分类在大数据驱动下的海洋天气预报

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753075

J. Anbarasi, V. Radha

引用次数: 0

Unsupervised Feature Learning for Text Pattern Analysis with Emotional Data Collection: A Novel System for Big Data Analytics 基于情感数据收集的文本模式分析的无监督特征学习:一种新的大数据分析系统

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753501

Dr. Yusuf Perwej, E. Bhuvaneswari, Saroj Kumar, V. Arulkumar, P. Nancy

{"title":"Unsupervised Feature Learning for Text Pattern Analysis with Emotional Data Collection: A Novel System for Big Data Analytics","authors":"Dr. Yusuf Perwej, E. Bhuvaneswari, Saroj Kumar, V. Arulkumar, P. Nancy","doi":"10.1109/ICACTA54488.2022.9753501","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753501","url":null,"abstract":"When it comes to our everyday life, emotions have a critical role to play. It goes without saying that it is critical in the context of mobile–computer interaction. In social and mobile communication, it is vital to understand the influence of emotions on the way people interact with one another and with the material they access. This lesson tried to investigate the relationship between the expressive state of mind and the efficacy of the human–mobile interaction while accessing a variety of different sorts of material over the course of the learning. In addition, the difficulty of the feeling of many individuals is taken into account in this research. Human hardness is an important factor in determining a person's personality characteristics, and the material that they can access will alter depending on how they engage with a mobile device. It analyses the link between the human-mobile interaction and the person's mental toughness in order to provide excellent suggestion material in the appropriate manner. In this study, an explicit feedback selection method is used to gather information on the emotional state of the mind of the participants. It has also been shown that the emotional state of a person's mind influences the human-mobile connection, with persons with varying levels of hardness accessing a variety of various sorts of material. It is hoped that this research will assist content producers in identifying engaging material that will encourage mobile users to promote good content by studying their personality features.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"27 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":"126675029","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

Comparative Analysis of CUK, SEPIC, Buck-Boost and ZETA Converters to Reduce Commutation Torque Ripple in BLDC Motor CUK、SEPIC、Buck-Boost和ZETA变换器减小无刷直流电机换相转矩脉动的比较分析

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753362

K. Balamurugan, V. Nandalal, G. Suresh, B. Shankar, B. Srirevathi

引用次数: 0

Deep Learning Techniques for Diabetic Retinopathy Diagnosis using Optical Coherence Tomography: A Review 使用光学相干断层扫描诊断糖尿病视网膜病变的深度学习技术:综述

2022 International Conference on Advanced Computing Technologies and Applications (ICACTA) Pub Date : 2022-03-04 DOI: 10.1109/ICACTA54488.2022.9753418

P. Jancy, B. Latha

引用次数: 1