2023 International Conference for Advancement in Technology (ICONAT)最新文献_第10页

Spatial Statistics-based Participant Selection for Optimised Mobile Crowd-Sensing 基于空间统计的优化移动人群感知参与者选择

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080362

Aditya Singh Sengar, Soumitra Debnath

{"title":"Spatial Statistics-based Participant Selection for Optimised Mobile Crowd-Sensing","authors":"Aditya Singh Sengar, Soumitra Debnath","doi":"10.1109/ICONAT57137.2023.10080362","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080362","url":null,"abstract":"Mobile Crowd-Sensing (MCS) is emerging as an important technology for future wireless networks and associated services like Mapping, Localization, Weather prediction, Pollution monitoring, etc. It is also being investigated for its potential in enabling the creation of Digital Twins of networks and cities as well. In MCS, few networked devices sense the parameter of interest and report it to a central entity, which utilizes this data to generate usable intelligence. For the MCS-based system to be reliable, it is imperative that the number and placement of the sensors are appropriate. If the number is less than adequate, the derived intelligence is not reliable. If the number is more, the additional data results in higher reporting and processing overheads. So, in order to realize the full potential of MCS without increasing the computational burden, in this work, a spatial statistics-based participant sensor selection scheme has been proposed. Radio Environment Mapping has been presented as an application of MCS. The number of participants is arrived at on the basis of the spatial correlation function. Then the participants are selected on the basis of the distance from the regular lattice centers. The results indicate a significant increase in accuracy in REM creation by the proposed method.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122398415","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

Web-Page Content Classification on Entropy Classifiers using Machine Learning 基于机器学习熵分类器的网页内容分类

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080462

S. Siddiqha, M. Islabudeen

{"title":"Web-Page Content Classification on Entropy Classifiers using Machine Learning","authors":"S. Siddiqha, M. Islabudeen","doi":"10.1109/ICONAT57137.2023.10080462","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080462","url":null,"abstract":"In recent years, the World Wide Web (WWW) has become a global data center, which permits people to store and distribute their information. The information in Web Pages may be related to be personal, official, commercial and business. The users of Web would like to access such information for their needs. Therefore, to use the Web data for any specific purpose, it is necessary to have techniques which will classify the Web Pages so that the suitable data available in Web Page are provided to users. This paper proposes a new technique for classification of Web Pages using level based classification and hierarchical indexing model based on predefined domains: Sports, Politics and education. The method works in two important phases: Training phase and Testing phase. During training phase the dynamic Feature Extraction and Knowledge Representation is performed. During testing phase the features extracted from the Web Pages are used for content matching for Classification. The technique comprises three steps namely: Dynamic Feature Extraction, Knowledge Representation and Classification for randomly distributed Web Pages. During Feature Extraction the important keywords are extracted from Headers and Paragraphs of Web Pages. The Frequency Occurrence of Key Words is determined and the frequency values are multiplied with weights so as to segregate the keywords at different priority levels. The Represented Knowledge is further used for content matching for classification of Web Pages. The percentage of belongingness of the webpage for each such category is calculated using Maximum Entropy Classifier. Maximum Entropy Classifier is considered due to its advantage in search based optimizations. The method is evaluated with three different categories of Web Page such as Sports, Politics and Education. The technique has achieved the Classification accuracy of 91% which is higher than conventional Classification technique.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122534398","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

Solution of Reactive Power Dispatch problems using Enhanced Dwarf Mongoose Optimization Algorithm 用增强型侏儒猫鼬优化算法求解无功调度问题

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080012

B. Dora, S. Bhat, Sudip Halder, M. Sahoo

{"title":"Solution of Reactive Power Dispatch problems using Enhanced Dwarf Mongoose Optimization Algorithm","authors":"B. Dora, S. Bhat, Sudip Halder, M. Sahoo","doi":"10.1109/ICONAT57137.2023.10080012","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080012","url":null,"abstract":"This paper proposes a hybrid metaheuristic algorithm for solving reactive power dispatch (RPD) problem. RPD is an optimization problem that minimizes the real power loss, total deviation in voltage and enhances the stability of voltage to secure and maintain an economical operating state in power system. In this paper, an enhanced local search capacity is achieved by incorporating the symbiotic organism search (SOS) into the Dwarf Mongoose optimization Algorithm (DMOA). The DMOA handles the exploration process in the proposed algorithm, while the mutualism phase and the DMOA’s local search process work together to solve the exploitation process. The suggested technique is used to find the best settings for minimizing actual power loss, total voltage variation, and L-Index. The MATLAB program has been developed for the objectives of the RPD problem and tested for IEEE 30 bus test system. The results of the proposed method are compared to those of various other algorithms including the original DMOA, and are shown to be superior. The efficiency and robustness of the hybrid algorithm is confirmed by the statistical analysis.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122541499","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

Axis Control of a Nonlinear Helicopter Model Using Intelligent Controller 基于智能控制器的非线性直升机模型轴向控制

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080707

A. Chaudhary

引用次数: 0

Application of Real-time Automatic Cartoon Style Generation from Live video 实时自动卡通风格生成的应用

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080457

G. M. Harshitha, Ramyashree, Vasudeva

引用次数: 0

Plotplay: An Automated Data Visualization Website using Python and Plotly Plotplay:一个使用Python和Plotly的自动数据可视化网站

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10079977

Z. Mundargi, Krisha Patel, Aayushi Patel, Rohan More, Sudhanshu Pathrabe, Shreyas D. Patil

{"title":"Plotplay: An Automated Data Visualization Website using Python and Plotly","authors":"Z. Mundargi, Krisha Patel, Aayushi Patel, Rohan More, Sudhanshu Pathrabe, Shreyas D. Patil","doi":"10.1109/ICONAT57137.2023.10079977","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10079977","url":null,"abstract":"Data visualization helps people see, interact with, and better understand any given data. Whether simple or complex, the right visualization can bring out excellent outcomes from the data and hence help a lot providing conclusions as well as pre-processing of the data to use it for Machine Learning or Artificial Intelligence algorithms. Nowadays, data visualization is required in every field. There are different interfaces available that are being used professionally worldwide. But, many still find it difficult to learn and get used to them due to their interface complexity or lack of programming knowledge, etc. So, in this paper we have provided the implementation of an easy-to-use website that will help users to visualize their data and find correlation between different variables by just one click. We have developed this website using python and its frameworks like Plotly, Flask along with HTML, CSS and JavaScript. It can be used by professionals but is mainly aimed for beginners who do not have much programming knowledge and find it difficult to deal with their datasets.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116685878","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

Design a System to Gain Optimum Solar Energy to Existing LV Distribution Transformer using Reactive Power Control Method in Sri Lankan PV Inverters 斯里兰卡光伏逆变器采用无功功率控制方法设计一种向现有低压配电变压器获得最佳太阳能的系统

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080682

U.S. Rahubadde, P.I. Eng. Widanapathirana, K.P.J.P. Eng Premathilaka, V.S. Galkissage, K.A.D.L. Ruwanga, J.G.K. Madusara, D.A.D. Weerakoon

{"title":"Design a System to Gain Optimum Solar Energy to Existing LV Distribution Transformer using Reactive Power Control Method in Sri Lankan PV Inverters","authors":"U.S. Rahubadde, P.I. Eng. Widanapathirana, K.P.J.P. Eng Premathilaka, V.S. Galkissage, K.A.D.L. Ruwanga, J.G.K. Madusara, D.A.D. Weerakoon","doi":"10.1109/ICONAT57137.2023.10080682","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080682","url":null,"abstract":"As a result of the increase in demand for electricity, renewable energy solutions like Photovoltaic (PV) generation portfolios are beneficial to both utility and consumers. It provides clean and green energy with no harmful emissions to the environment. Although PV generation gives a solution for the energy problem, it might also have adverse effects. High penetration of PV can raise the feeder voltage level, especially in light load conditions. Active power curtailing methods are used today to maintain voltage regulation, and because of that, there is a limitation of connecting solar distribution generators within a specific feeder. Hence the Volt/Var control mechanism can be introduced to gain optimum solar energy from PV generation while reactive power is considered. In this paper, the current Low Voltage (LV) network with PV generators in a specific area is modelled and analyzed using the open-source simulation tools OpenDSS and Matlab. An MV (Medium Voltage)/ LV transformer and a three-phase feeder are used to demonstrate the usefulness of the proposed simulation model considering several existing domestic consumers. In practice, Smart inverters have that reactive power enabling mode, and this research gives an idea which is how to compensate the reactive power absorption from the grid to the known desired value. This study aims to construct a program to develop a system to enable reactive power mode within the network of domestic PV users when needed. As a result, with this Volt/Var control of the inverter, more solar DG’s (Distribution Generators) can be connected to a feeder rather than the present situation.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116907697","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

Benign and Malignant Skin Lesion Detection from Melanoma Skin Cancer Images 基于黑色素瘤皮肤癌图像的良恶性皮肤病变检测

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080355

Shagun Sharma, Kalpna Guleria, Sushil Kumar, S. Tiwari

{"title":"Benign and Malignant Skin Lesion Detection from Melanoma Skin Cancer Images","authors":"Shagun Sharma, Kalpna Guleria, Sushil Kumar, S. Tiwari","doi":"10.1109/ICONAT57137.2023.10080355","DOIUrl":"https://doi.org/10.1109/ICONAT57137.2023.10080355","url":null,"abstract":"Skin cancer is the most dangerous and lethal cancer that affects millions of people each year. The accurate identification of skin cancers can not be accomplished without expert dermatologists. However, specific research studies of WHO in Canada, US and Australia, show that in the year 1960s to 1980s, the cases of skin cancer has noted more than two times increased in comparison with the previous years. The identification of skin cancer in its early stage is an expensive and difficult task because it doesn’t cause too much bad in the initial phase. Whereas, the growth of skin cancer requires biopsy and many other treatments each time which is quite costly as per the statistics of India. This challenge makes it a necessary step to identify the existence of skin cancer in the early stages to increase immortality. With the evolution and progression in technology, there are various methods which have participated in and solved medical issues including covid19, pneumonia and many others. Similarly, machine learning(ML) and deep learning(DL) models are applicable to diagnosing skin cancer in its early stages. In this work, the support vector machine (SVM), naive bayes (NB), K-nearest neighbour (KNN) and neural networks(NN) have been used for classifying benign and malignant lesions. Furthermore, for the feature extraction from the dataset, a pre-trained SqueezeNet model has been used. The classification results of KNN, SVM, NB and NN have been shown in the accuracy, recall, F1-Measure, precision, AUC and ROC. The comparison of the models has resulted that the NN model outperforms all other models when applied with the SqueezeNet feature extractor with the highest accuracy, F1-Measure, recall, precision and AUC as 88.2%, 0.882, 0.882, 0.882 and 0.957, respectively. Lastly, the performance metrics analogies results of each model have been illustrated for the classification of benign and malignant lesions.","PeriodicalId":250587,"journal":{"name":"2023 International Conference for Advancement in Technology (ICONAT)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116972099","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

Envisaging and Retaining College Workforce Attrition using Machine Learning and Ensemble Learning 利用机器学习和集成学习设想和保留大学劳动力流失

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080463

Avinash L. Golande, Vasudev Surwase, Neha Patil, Janhvi Bhandekar, Jay Shinde

引用次数: 0

Place Recognition Systems by Old Photos using Machine Learning Algorithm 基于机器学习算法的旧照片位置识别系统

2023 International Conference for Advancement in Technology (ICONAT) Pub Date : 2023-01-24 DOI: 10.1109/ICONAT57137.2023.10080180

Prashant Ghulappanavar, H. Shanavas

引用次数: 0