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Estimation of Precision in Fake News Detection Using Novel Bert Algorithm and Comparison with Random Forest 基于Bert算法的假新闻检测精度估计及与随机森林的比较
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917629
S. M, Kaliyamurthie K. P
{"title":"Estimation of Precision in Fake News Detection Using Novel Bert Algorithm and Comparison with Random Forest","authors":"S. M, Kaliyamurthie K. P","doi":"10.1109/ICICICT54557.2022.9917629","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917629","url":null,"abstract":"This study aims to improve the prediction rate with a novel model of bidirectional encoder representation for transformers (BERT) compared with random forest algorithm. A dataset of size 1100 is used to compare Novel BERT's performance with Random Forests. With Random Forest, a framework for identifying fake news in electronic media networks is proposed. clinical calculates a sample size of 20 according to the framework. Regarding to Precision rate, the Novel Bert algorithm beats the Random Forest algorithm by 8.33%. In comparison to the random forest algorithm, BERT achieves a rate of 0.002 that is significantly better than it. It is concluded that the novel BERT algorithm outperforms Random Forest predicting of fake information in this study.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121809373","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
Copy Move Forgery Detection Methods and Its Advantage of Two Stage Filtering 两阶段滤波的复制移动伪造检测方法及其优点
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9918014
Devika A D, Bindhu K. Rajan
{"title":"Copy Move Forgery Detection Methods and Its Advantage of Two Stage Filtering","authors":"Devika A D, Bindhu K. Rajan","doi":"10.1109/ICICICT54557.2022.9918014","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9918014","url":null,"abstract":"In the modern information system, digital media altering has become a major serious issue. Different ways of manipulating information methods are available like slicing, copy move forgery methods etc. Here mainly focusing on copy forgery methods based on key point based and their detection methods. This paper also shows the advantage of Two stage filtering detection method over detection method is also discussed. In two stage filtering four stages are involved. First key point extraction is done using a key point extraction algorithm, next step is finding matched key points are filtered by key point- matching algorithm and third is a Two stage algorithm based on Two stage filtering and the Clustering-Based Filter (CBF), is applied to eliminate most of the falsely detected key point pairs and finally removing falsely matched key point pairs and finding the forged region.This paper mainly covers the comparison and review of CMFD methods.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116706345","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
Flower Leaf Image Classification using Machine Learning Techniques 利用机器学习技术进行花叶图像分类
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917823
Bittu Kumar Aman, Vipin Kumar
{"title":"Flower Leaf Image Classification using Machine Learning Techniques","authors":"Bittu Kumar Aman, Vipin Kumar","doi":"10.1109/ICICICT54557.2022.9917823","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917823","url":null,"abstract":"As per the report of Statista, more than 50,000 thousand categories of flower species exist worldwide; here, the problem arises identification of each type so that we can know the real advantages or the natural goodness of the flower plants. It is challenging to identify the flowers without prior knowledge/expertise. Therefore, it is crucial to make the effect and automated systems to classify the different flowers using their leaf images. This research collected 25 different categories of flowers and plants leaf images, which are 6619 total RGB images. Six classical machine learning algorithms have been utilized for the classification like K-Nearest Neighbours (KNN), Linear Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Naïve Bayes (NB), and Multilayer Perceptron (MLP). The comparative study of the classifier’s performances has been done based on classification accuracy, precision, recall, and F1-score. This research aims to find an effective machine learning classification algorithm that can be utilized for automation. The analysis of the results shows that the MLP classifier has the highest classification accuracy, i.e., 89.61%. The confusion matrix of MLP performance has been analyzed and has identified that similar shaped and textured leaves are usually misclassified.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121279619","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
Efficientnet for Brain Tumor Detection from MRI 高效的MRI脑肿瘤检测方法
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917728
G. Gayathri, S. Sindhu
{"title":"Efficientnet for Brain Tumor Detection from MRI","authors":"G. Gayathri, S. Sindhu","doi":"10.1109/ICICICT54557.2022.9917728","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917728","url":null,"abstract":"The human brain is the primary controller of the humanoid system. The unusual expansion of the brain tissues leads to brain tumor. The continuous escalation of brain tissue leads to brain cancer. Computer vision plays an inevitable role in the field of medical science, and, in it, magnetic resonance imaging techniques are used to detect brain tumors. In the realm of image categorization, deep learning is a core topic. It currently has quite a promising potential in terms of brain tumor classification and segmentation. This work’s key principle is to build a deep convoultional neural network for detecting brain tumors. In the proposed model, the tumor region is first segmented from the MR images. Second, data augmentation is used to allow effective training, and, subsequently, a fine-tuned model EfficientNet is used for detecting multi-class brain tumor. The model is trained using brain tumor dataset. The method achieved an average accuracy of 97.35%.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126094390","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
Enhancement of Power Quality in Weak Grid Fed Wind Energy System by using ANFIS Controller 利用ANFIS控制器提高弱电网风电系统电能质量
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917759
V. M, P. B
{"title":"Enhancement of Power Quality in Weak Grid Fed Wind Energy System by using ANFIS Controller","authors":"V. M, P. B","doi":"10.1109/ICICICT54557.2022.9917759","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917759","url":null,"abstract":"The manuscript discusses the implementation of adaptive-neural-fuzzy-interface-system in the wind energy systems to control the speeds of the generator driven by the interconnected wind turbine. The generator speeds are regulated using the voltage-source converters connected back to back on machine side and grid side points. This paper also proposes the strategy to subside the harmonics and improve the power quality by implementing the integrator for grid side converter switching and DC offset rejections. Under the transient- conditions of overshoot, the FLC tracks the reference speed meant for the synchronous-generator to keep the system under control thereby improving the wind-feed turbine variables with reduced-oscillations and balanced-operations. The power generated from the turbine system is fed to grid in support of the maintaining the grid reliability and continuity in demand supply. The simulation results were presented from MATLAB simulations with various variables taking into consideration for efficiency and performance.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123801511","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
Secure Node Covering of Cocktail Party Graphs and Generalized Fan Graphs 鸡尾酒会图和广义扇形图的安全节点覆盖
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9918002
D. Angel, I. A. Arputhamary, R. Revathi, M. Nirmala
{"title":"Secure Node Covering of Cocktail Party Graphs and Generalized Fan Graphs","authors":"D. Angel, I. A. Arputhamary, R. Revathi, M. Nirmala","doi":"10.1109/ICICICT54557.2022.9918002","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9918002","url":null,"abstract":"Combinatorial problems have become more important recently in the study of coverage, connectivity, and fault tolerance in communication networks. A communication network's topology is often modelled as an undirected graph G = (V, E) in which the set of vertices V and the set of edges E correspond to nodes and links of the network respectively. The key idea behind the notion of vertex covering is to minimize the number of nodes with the property that, all the communication links in the network are secure. To achieve this operation, nodes in the minimum vertex cover set are trusted and can monitor transmission between nodes, since every communication link will be under the coverage of one or more nodes. This paper analyses the vertex and edge covers of Cocktail Party and Generalized Fan Graphs.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115099648","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
Segmentation Of Biological Cells In Microscopic Images 显微图像中生物细胞的分割
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917840
Sai Teja Kolipaka, Arush Karingala, Sandeep Reddy Lingala, Mohammed Ayub Ashraf, K. Manisha
{"title":"Segmentation Of Biological Cells In Microscopic Images","authors":"Sai Teja Kolipaka, Arush Karingala, Sandeep Reddy Lingala, Mohammed Ayub Ashraf, K. Manisha","doi":"10.1109/ICICICT54557.2022.9917840","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917840","url":null,"abstract":"Image analysis of cells is an important aspect for research in biomedical applications. Image segmentation is the important step in image analysis. The task is not so easy as to identify the cells as there a lot of complexities like the removal of background noise, overlapping of cells, and change in the position of the cell. This paper examines and analyses various methods for pre-processing and segmentation using metrics, which are used to study the shape, size and behavior of the cells. First step is the pre-processing to reduce the noise present in the image. Then the pre-processed image is taken as the input and the cells in the image are segmented. The compared results of various techniques by measuring the accuracy, Jaccard index and number of cells detected in the image.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116574409","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 and Development of I-Shaped Structure Antenna for Wireless Communications 无线通信用i型结构天线的设计与研制
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917664
S. Kannadhasan, Jacob Abraham, R. Nagarajan
{"title":"Design and Development of I-Shaped Structure Antenna for Wireless Communications","authors":"S. Kannadhasan, Jacob Abraham, R. Nagarajan","doi":"10.1109/ICICICT54557.2022.9917664","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917664","url":null,"abstract":"In this work, an I-shaped microstrip patch antenna with excellent bandwidth and gain for various wireless applications is proposed. The suggested structure would span the frequency range of I-Shaped microstrip patch antennas, which is 2 GHz to 11 GHz. The suggested antenna, made of FR4 and having a dielectric constant of 2.4, is powered by a microstrip line. Radar, satellite communication, medical applications, remote sensing, wireless communication, and other applications may all benefit from this antenna. In order to increase transmission and reception, a gadget needs an antenna. It will also use less energy, be more efficient, and last longer. The suggested I-patch antenna has lower return losses at resonance frequencies of 2 GHz and 11 GHz, which makes it suitable for GPS and other band applications. The bandwidth of the first resonating frequency is 2 GHz, while the bandwidth of the second is 11 GHz. Performance metrics for the recommended antenna include return loss, VSWR, radiation pattern, and directivity. The HFSS programme is used to design and test antennas.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"324 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122735334","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
Carbon Capture, Utilization and Storage (CCUS) - The Energy source of the future 碳捕获、利用和封存(CCUS)——未来的能源
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9918005
G. Glan Devadhas, D. M. Mary Synthia Regis Prabha, A. Gayathri, M. M. Shinu, M. Dhanoj
{"title":"Carbon Capture, Utilization and Storage (CCUS) - The Energy source of the future","authors":"G. Glan Devadhas, D. M. Mary Synthia Regis Prabha, A. Gayathri, M. M. Shinu, M. Dhanoj","doi":"10.1109/ICICICT54557.2022.9918005","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9918005","url":null,"abstract":"Transformation of global energy sector from fossil fuel based energy production and consumption to renewable energy sources has lead to energy transition. This energy transition also aims to reduce the green house gases through various forms of decarbonization. Fossil fuels are excellent fuels and cannot be replaced immediately because of their incredible energy density, requiring no innovation to collect, store and transform into energy and the well-established structures which made the industrial revolution possible. Hence to achieve net carbon zero condition across the globe, the emitted CO2 from the fossil fuel plants is collected, stored and is either used in applications requiring CO2 as the raw material or can be permanently sequestrated in CO2 storage sites utilizing Carbon Capture, Utilization and Storage (CCUS) technology. The captured CO2 is used for producing further energy thus improving the hydrogen economy and also is utilized for Enhanced Oil Recovery (EOR) which makes this CCUS technology the energy source of the future.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122466795","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
A Comparative Study of Machine Learning Algorithms for Photovoltaic Degradation Rate Prediction 光伏退化率预测的机器学习算法比较研究
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Pub Date : 2022-08-11 DOI: 10.1109/ICICICT54557.2022.9917960
Bhavya Dhingra, Shivam Tyagi, A. Tomar
{"title":"A Comparative Study of Machine Learning Algorithms for Photovoltaic Degradation Rate Prediction","authors":"Bhavya Dhingra, Shivam Tyagi, A. Tomar","doi":"10.1109/ICICICT54557.2022.9917960","DOIUrl":"https://doi.org/10.1109/ICICICT54557.2022.9917960","url":null,"abstract":"Solar energy is the most versatile, harmless, and non-exhaustive energy present in nature because of this, the number of photovoltaic modules that have been integrated into the electrical grid is increasing every day. As a result, reliable forecasting of falling power output over the period of time is required for an acceptable return on investment made for these interactions, to estimate the power delivered to the power system by these photovoltaic modules, photovoltaic degradation rates must be known. In this study degradation rates of photovoltaic modules are estimated using the application of nine machine learning models and the effectiveness of these models is compared in order to determine which model is most efficient. All the models are tested on various evaluation metrics like mean absolute error, root mean squared error, and mean percentage error for an unbiased evaluation, and the run time of these models is also calculated and compared to determine the overall efficiency of the models.","PeriodicalId":246214,"journal":{"name":"2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122956412","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
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