2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)最新文献_第2页

A Novel Approach to Ambiguous Fake News Classification through Machine Learning 一种基于机器学习的模糊假新闻分类新方法

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972102

Sanai Divadkar, Akshat Sahu, Shalini Puri

{"title":"A Novel Approach to Ambiguous Fake News Classification through Machine Learning","authors":"Sanai Divadkar, Akshat Sahu, Shalini Puri","doi":"10.1109/GCAT55367.2022.9972102","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972102","url":null,"abstract":"The rise of digitalization and technology has substantially expanded the number of people with online news access, resulting in a significant shift in how information is consumed on social channels. The spread of fake news with ambiguity is a critical and harmful aspect of handling online news access. Such news should be identified quickly since it can harm an individual or organization's reputation and holds the capacity to influence one's actions which can be a potential threat to modern civilization. The proposed work in this paper presents an ambiguous fake news classification model using the decision tree, random forest, and SVM. It first pre-processed the known dataset, extracted its features, and then provided the training to all three classifiers. Further, the classifiers were tested against unknown datasets. The experiments were performed on the collected dataset of 40,000 records including fake and real news. It is observed that it achieved very promising experimental results of precision, recall, and accuracy. It obtained the best results with the decision tree, that is, 0.9977 for both precision and recall along with 99.67% accuracy.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117299871","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

Automatic Attendance System Using Artificial Intelligence 人工智能自动考勤系统

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972201

G. Pooja, K. Rekha

引用次数: 0

GMM-based Document Clustering of Knowledge Graph Embeddings 基于gmm的知识图嵌入文档聚类

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972216

R. Menon, S. D. Kumar, CR Vismaya

{"title":"GMM-based Document Clustering of Knowledge Graph Embeddings","authors":"R. Menon, S. D. Kumar, CR Vismaya","doi":"10.1109/GCAT55367.2022.9972216","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972216","url":null,"abstract":"Digital technology and World Wide Web have re-sulted in a growth in the number of digital documents. The ma-jority of the data is unstructured, and extracting information into a structured machine-readable format remains a difficult under-taking. Clustering, which automatically categorizes information into meaningful groupings, is one of the most important activ-ities. Several information extraction and information gathering applications use document clustering. Document clustering is an unsupervised method for dividing a big corpus of documents into smaller, meaningful, identifiable, and verifiable sub-groups. But capturing the semantics of the documents is still an open problem. A knowledge graph can represent the relationships between the entities in the document collection. But a knowledge graph gets extremely dense and high-dimensional as the amount of data increases, requiring significant processing resources. We aim to explore this problem by using Knowledge Graph Embedding (KGE), which maps the high-dimensional representation into a compute-efficient low-dimensional embedded representation and then cluster these embeddings using the Gaussian Mixture Model (GMM)-based clustering technique. Dimensionality reduction of the embeddings has been done using t-SNE. We have found that the silhouette coefficient has improved considerably for t-SNE based GMM clustering as compared to Kmeans clustering alone.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116334793","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

Automatic Flight Plan Generation for UAV-Assisted Elevated Meter Reading using Ant Colony Optimization 基于蚁群优化的无人机辅助高架抄表自动飞行计划生成

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972104

Jose Eduardo B. Cerillo, Rizza T. Loquias, S. Fenomeno

{"title":"Automatic Flight Plan Generation for UAV-Assisted Elevated Meter Reading using Ant Colony Optimization","authors":"Jose Eduardo B. Cerillo, Rizza T. Loquias, S. Fenomeno","doi":"10.1109/GCAT55367.2022.9972104","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972104","url":null,"abstract":"This paper presents the development of an Ant Colony Optimization (ACO)-based UAV flight plan generator for Automatic Electric Meter Reading (AMR) at elevated metering centers (EMC). The program's flight plan against a UAV human operator flight plans were compared for different missions and considering the following: coordinate location of EMCs, the number of electric meters within the EMC, the UAV's takeoff and landing location, the EMC's height, the UAV's position relative to the EMC during data collection, and the UAV's battery capacity. The generated flight plan captures the most EMC data in the shortest time possible, automatically. Tests conducted include the Shortest Route Test and the Largest Amount of Data per Unit Time test that compared the program's and human operator's flight plan development and mission completion times. Results revealed that the program's flight plan is 30.58 percent more efficient than the UAV human operator's during the Shortest Route Test and 28.10 percent more efficient during the Largest Amount of Data per Unit Time test.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114799137","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

Deep Learning Based Predictive Analysis of BLDC Motor Control 基于深度学习的无刷直流电机控制预测分析

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972193

T. Porselvi, Sr Y Aouthithiye Barathwaj, S. Cs, S. V. Tresa Sangeetha, J. Shalini Priya

{"title":"Deep Learning Based Predictive Analysis of BLDC Motor Control","authors":"T. Porselvi, Sr Y Aouthithiye Barathwaj, S. Cs, S. V. Tresa Sangeetha, J. Shalini Priya","doi":"10.1109/GCAT55367.2022.9972193","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972193","url":null,"abstract":"Predictive Analysis using deep learning techniques are emerging in several engineering domains. Artificial Neural Networks consists of network of layers to learn, process and predict from the data. Their implementation in electrical and electronics engineering has consistently helped in producing intelligent industries with effective results. The brushless direct current (BLDC)motor generates magnetic fields by switching DC current to the motor windings using electronic closed-loop controllers. BLDC motors require low maintenance, and exhibit high speed and sufficient torque capacity and hence are used in various applications. This motor has an edge over other motors because of its superior performance and ease with which the power converters can regulate its speed. This article describes a technique for varying the speed of a BLDC motor that involves altering the voltage of bridge converter, which feeds the motor winding. The speed control is carried out with a speed controller (PI-based). The motor is modelled in MATLAB/Simulink, and a PI controller is employed to provide the speed control. Simulated waveforms of EMF signals are achieved along with rotor speed, Hall Effect signals, electromagnetic torque, and PWMsignals. Artificial neural networks (ANN) are used to forecast the corresponding parameters, and they are fed with the gathered data to produce results that are reasonably close to the results from the simulations. Hence, both the simulation-based approach as well as the predictions from the data provided, yield satisfactory outcomes.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124370096","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: 11

Development of Verification IP of Physical Layer of PCIe PCIe物理层验证IP的开发

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971846

Viraj Nitin Vaidya, V. Ingale, Ashlesha Gokhale

引用次数: 0

Deep Learning-Based Bone Age Estimation Using X-Ray Hand Images 基于x射线手部图像的深度学习骨龄估计

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971842

K. Ramanjaneyulu, Sri. L Manju, M. Sohit, M. Vikas, S. Yaswanth

引用次数: 0

Design and Analysis of Underwater Bifacial Solar Photovoltaic Cell 水下双面太阳能光伏电池设计与分析

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971927

Suraj Naik, S. Kulkarni

引用次数: 0

Implementation of Battery and Ultra capacitors Based storage for Electric Vehicle system 基于电池和超级电容器的电动汽车存储系统的实现

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972185

Jalaj Tyagi, S. Yadav, Shakuntla Boora, Poonam Singhal

{"title":"Implementation of Battery and Ultra capacitors Based storage for Electric Vehicle system","authors":"Jalaj Tyagi, S. Yadav, Shakuntla Boora, Poonam Singhal","doi":"10.1109/GCAT55367.2022.9972185","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972185","url":null,"abstract":"Uplifting of the Electrical vehicle technology allow drastic change toward the green energy system and make environment pollution free, although nowadays government taking many initiatives toward development of the Electric Vehicle (EV) technology and by 2030‘s electric vehicle should occupy all of the space of the Internal Combustion Engine (ICEs). EVs allow to move toward sustainability and also make environment free from carbon emission. As fossil fuel consumption is directly proportional to the amount of carbon emit into the environment. EVs work with the principle of the Electric system which can be directly link to the resources used in the generation of the electricity if the resources used to generate electricity could be renewable energy, then sustainability toward development of the environment pollution free can be attain 100 %. While discussing EVs give direct highlight on the Energy Storage and the type of energy storage using in the EVs. Generally, Lithium-Ion batteries increasing extensively in the EVs market due to their excellent performance. On the other hand, supercharge capacitor or ultra-capacitor also creating significant impact toward growth of the electric mobility market. As Ultra capacitor characteristic provide criteria to fit into the Electric mobility market such as high Efficiency, High Temperature stability, instantly charge and discharge without dropping in the performance. Generally, batteries have low specific power but high specific storage system can be attained with the implementation of the ultracapacitor to the Energy storage System and allow to develop the Hybrid topology of the Energy system which can be used to reduce the jerk load /power utilization in the vehicle in the terms of acceleration/deceleration and also flow of energy in the regeneration process. This paper provides an extensive implementation of the hybrid energy storage System (Battery along with Ultra capacitors)with regeneration of the energy toward energy storage.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122252185","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

Implementation of Automotive Sensor Tester for Engineers at OEMs and Vehicle Service Agencies using Raspberry Pi 使用树莓派为oem和汽车服务机构的工程师实现汽车传感器测试仪

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972090

P. Kumar, G. Murthy

引用次数: 0