Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938189
Ankita Raj, S. K. Singh
The gross domestic product (GDP), a key indicator of an economy's index, is a market estimate of all final services and items produced within a country. This research aims to analyze, compare, and forecast the GDP of India's neighboring countries (Pakistan, Nepal, Bangladesh, and China). As a result, this paper employs an autoregressive integrated moving average (ARIMA) model, Auto-ARIMA and regression model. These models used to do train with data to better compare with different countries and forecast future values. Performance is analyzed through RMDSPE, AE, MAPE, NRMSE and RMSPE, and forecasted the countries' GDP as mentioned above from 2021 to 2026. Further, policy implications are also suggested.
{"title":"Forecasting GDP of India and its neighbouring countries using Time Series Analysis","authors":"Ankita Raj, S. K. Singh","doi":"10.1109/GlobConPT57482.2022.9938189","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938189","url":null,"abstract":"The gross domestic product (GDP), a key indicator of an economy's index, is a market estimate of all final services and items produced within a country. This research aims to analyze, compare, and forecast the GDP of India's neighboring countries (Pakistan, Nepal, Bangladesh, and China). As a result, this paper employs an autoregressive integrated moving average (ARIMA) model, Auto-ARIMA and regression model. These models used to do train with data to better compare with different countries and forecast future values. Performance is analyzed through RMDSPE, AE, MAPE, NRMSE and RMSPE, and forecasted the countries' GDP as mentioned above from 2021 to 2026. Further, policy implications are also suggested.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130923369","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938363
Abinash Nanda, Nityananda Giri, P. Nayak, R. Mallick, Sairam Mishra, A. Choudhury
Increasing penetration of renewable energy sources in microgrid increases the complexity of coordinated control and protection issues. Differential protection seems to be reliable and accurate. This research proposed a new differential protection scheme to detect different types of series and shunt faults using rate of change of apparent power. This proposed technique has been implemented using MATLAB with a standard microgrid test system. Simulation results show that the proposed method is able to detect faults with less detection time and higher accuracy.
{"title":"Differential Protection of Microgrid based on Rate of Change of Apparent Power","authors":"Abinash Nanda, Nityananda Giri, P. Nayak, R. Mallick, Sairam Mishra, A. Choudhury","doi":"10.1109/GlobConPT57482.2022.9938363","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938363","url":null,"abstract":"Increasing penetration of renewable energy sources in microgrid increases the complexity of coordinated control and protection issues. Differential protection seems to be reliable and accurate. This research proposed a new differential protection scheme to detect different types of series and shunt faults using rate of change of apparent power. This proposed technique has been implemented using MATLAB with a standard microgrid test system. Simulation results show that the proposed method is able to detect faults with less detection time and higher accuracy.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131111014","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938175
L. Kanagasabai
In this paper Quantum based Northern rockhopper penguin Optimization (QNPO) Algorithm is smeared for resolving the loss diminishing problem. Northern rockhopper penguin implements clustering, in the progression of perilous winters for sustain. Northern rockhopper penguin accomplishes gathering to conserve their zing and exploits on tuft in elevated temperature. Elevated temperature grade supports to realize exploration and exploitation trade between Northern rockhopper penguins. Quantum mechanics has been combined with Northern rockhopper penguin Optimization Algorithm. Proposed QNPO Algorithm is corroborated in IEEE systems.
{"title":"Quantum based Northem Rockhopper Penguin Optimization Algorithm for Power Loss Diminution","authors":"L. Kanagasabai","doi":"10.1109/GlobConPT57482.2022.9938175","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938175","url":null,"abstract":"In this paper Quantum based Northern rockhopper penguin Optimization (QNPO) Algorithm is smeared for resolving the loss diminishing problem. Northern rockhopper penguin implements clustering, in the progression of perilous winters for sustain. Northern rockhopper penguin accomplishes gathering to conserve their zing and exploits on tuft in elevated temperature. Elevated temperature grade supports to realize exploration and exploitation trade between Northern rockhopper penguins. Quantum mechanics has been combined with Northern rockhopper penguin Optimization Algorithm. Proposed QNPO Algorithm is corroborated in IEEE systems.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126506117","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938332
Ritesh Gupta, S. Ghatakchoudhuri
This article shows a Three-Phase, Four-Wire (3P4W) AC mains supportive single-stage, Solar Photovoltaic-Battery Energy Storage-Voltage Source Converter (SPV-BES-VSC) based Distributed Energy Generation System (DEG) to accomplish multiple functions, is presented using Double Reduced Order Generalised Integrator (DROGI). DROGI based Current Control performs multi-tasking such as, power factor correction and eliminates zero sequence harmonic from the neutral wire. One of the ROGI functions is to produce the 50 Hz peak component from the distorted, balanced/unbalanced load current. The purpose of another ROGI is to generate a sinusoidal unit template for reference AC mains current, even if sag/swell occurs at the Point of Common Coupling (PCC). BES system is protected from overcharge/deep discharge by using a Energy Management System (EMS). The complete control algorithm is realised in MATLAB in Discrete Time Frame (DTF) using simulink and Sim Power System (SPS) toolboxes for different operating conditions. The Total Harmonic Distortion (THD) of AC mains current is noticed within 5% according to IEEE-519 and 929, respectively.
本文介绍了一种基于双降阶广义积分器(DROGI)的分布式发电系统(DEG)，该系统支持单级太阳能光伏-电池储能-电压源转换器(spv - es - vsc)的三相四线(3P4W)交流电源，可实现多种功能。基于DROGI的电流控制执行多任务，如功率因数校正和消除零线的零序谐波。ROGI的功能之一是从扭曲的、平衡的/不平衡的负载电流中产生50 Hz的峰值分量。另一个ROGI的目的是为参考交流电源电流生成正弦单元模板，即使在共耦合点(PCC)发生凹陷/膨胀。BES系统通过使用能量管理系统(EMS)来防止过充/深度放电。采用simulink和Sim Power System (SPS)工具箱，在MATLAB中实现了离散时间框架(DTF)下的完整控制算法。根据IEEE-519和ieee - 929，交流市电电流的总谐波失真(THD)在5%以内。
{"title":"A Multi-Functional, 3P4W Utility Integrated Single- Stage Distributed Generating System With DROGI Based Control Approach","authors":"Ritesh Gupta, S. Ghatakchoudhuri","doi":"10.1109/GlobConPT57482.2022.9938332","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938332","url":null,"abstract":"This article shows a Three-Phase, Four-Wire (3P4W) AC mains supportive single-stage, Solar Photovoltaic-Battery Energy Storage-Voltage Source Converter (SPV-BES-VSC) based Distributed Energy Generation System (DEG) to accomplish multiple functions, is presented using Double Reduced Order Generalised Integrator (DROGI). DROGI based Current Control performs multi-tasking such as, power factor correction and eliminates zero sequence harmonic from the neutral wire. One of the ROGI functions is to produce the 50 Hz peak component from the distorted, balanced/unbalanced load current. The purpose of another ROGI is to generate a sinusoidal unit template for reference AC mains current, even if sag/swell occurs at the Point of Common Coupling (PCC). BES system is protected from overcharge/deep discharge by using a Energy Management System (EMS). The complete control algorithm is realised in MATLAB in Discrete Time Frame (DTF) using simulink and Sim Power System (SPS) toolboxes for different operating conditions. The Total Harmonic Distortion (THD) of AC mains current is noticed within 5% according to IEEE-519 and 929, respectively.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116917785","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938221
P. Saji, A. Muhammed, V. V.
Power transformers are an inevitable and expensive equipment in an electrical power system. Condition monitoring uses predictive analysis to determine whether a problem is present or absent in order to prevent transformer failures and guarantee the transformer's safe operation. Among various condition monitoring techniques, Sweep Frequency Response Analysis (SFRA) is a powerful and reliable tool to detect winding deformations. However, the diagnosing potential of SFRA is still its infant state. Any mechanical damage in the transformer winding will change the equivalent circuit parameters and this change will be reflected in the FRA traces. By comparing the FRA traces of the testing transformer with normal winding the fault can be detected. To locate and quantify the axial displacement these FRA traces need to be acknowledged precisely. Support Vector Machine (SVM), a supervised machine learning technique helps to locate and quantify the axial displacement with the help of features extracted from the FRA traces of testing transformer and nominal winding. A series of axial displacements is simulated in FEMM Software and corresponding equivalent circuit parameters are used to generate FRA traces. Furthermore, features are extracted from these FRA traces to train the SVM model to enable it to predict the location and quantity of axial displacement accurately. Finally, the accuracy of this SVM model is tested through randomly created axial displacements data. The result indicates the ability of this technique to be used as an intelligent and accurate diagnostic tool.
{"title":"An Efficient Method to Localize and Quantify Axial Displacement in Transformer Winding Using Support Vector Machines","authors":"P. Saji, A. Muhammed, V. V.","doi":"10.1109/GlobConPT57482.2022.9938221","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938221","url":null,"abstract":"Power transformers are an inevitable and expensive equipment in an electrical power system. Condition monitoring uses predictive analysis to determine whether a problem is present or absent in order to prevent transformer failures and guarantee the transformer's safe operation. Among various condition monitoring techniques, Sweep Frequency Response Analysis (SFRA) is a powerful and reliable tool to detect winding deformations. However, the diagnosing potential of SFRA is still its infant state. Any mechanical damage in the transformer winding will change the equivalent circuit parameters and this change will be reflected in the FRA traces. By comparing the FRA traces of the testing transformer with normal winding the fault can be detected. To locate and quantify the axial displacement these FRA traces need to be acknowledged precisely. Support Vector Machine (SVM), a supervised machine learning technique helps to locate and quantify the axial displacement with the help of features extracted from the FRA traces of testing transformer and nominal winding. A series of axial displacements is simulated in FEMM Software and corresponding equivalent circuit parameters are used to generate FRA traces. Furthermore, features are extracted from these FRA traces to train the SVM model to enable it to predict the location and quantity of axial displacement accurately. Finally, the accuracy of this SVM model is tested through randomly created axial displacements data. The result indicates the ability of this technique to be used as an intelligent and accurate diagnostic tool.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125288117","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938296
Zhipeng Qi, Md. Ashib Rahman, Md. Rabiul Islam
The magnetic linked multiport converter (MLMC) has high degree of control flexibility and can be operated as an effective interface for renewable energy integration to the traditional power grid and electric vehicle charging. Unlike the traditional magnetic linked dual port converters, the MLMC provides multiple ports, which share a common magnetic link. The MLMC has soft-switching ability, ensures galvanic isolation, and facilitates high-density power transmission. For the robust and effective operation of the MLMC, the voltages at the multiple ports should be perfectly balanced under rapid load change conditions so that the ports can be accessed in a plug-n-play manner. The traditional linear controller suffers from high voltage overshoot and undershoot under abrupt load change and the controller can be saturated which in turn makes the system unbalance. In this paper, a model predictive control technique is developed and proposed first time for the MLMC to ensure robust voltage control. The performance of the controller is tested under different load change conditions at different ports of the MLMC. The results show that the controller effectively balances the voltages under varying loads connected to the MLMC at random time interval. Moreover, with the predictive controller, the voltages achieves very fast dynamic response and do not show any significant voltage overshoot and undershoot, which indicates the superiority of the controller.
{"title":"Model Predictive Control for Magnetic Linked Multiport Converter","authors":"Zhipeng Qi, Md. Ashib Rahman, Md. Rabiul Islam","doi":"10.1109/GlobConPT57482.2022.9938296","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938296","url":null,"abstract":"The magnetic linked multiport converter (MLMC) has high degree of control flexibility and can be operated as an effective interface for renewable energy integration to the traditional power grid and electric vehicle charging. Unlike the traditional magnetic linked dual port converters, the MLMC provides multiple ports, which share a common magnetic link. The MLMC has soft-switching ability, ensures galvanic isolation, and facilitates high-density power transmission. For the robust and effective operation of the MLMC, the voltages at the multiple ports should be perfectly balanced under rapid load change conditions so that the ports can be accessed in a plug-n-play manner. The traditional linear controller suffers from high voltage overshoot and undershoot under abrupt load change and the controller can be saturated which in turn makes the system unbalance. In this paper, a model predictive control technique is developed and proposed first time for the MLMC to ensure robust voltage control. The performance of the controller is tested under different load change conditions at different ports of the MLMC. The results show that the controller effectively balances the voltages under varying loads connected to the MLMC at random time interval. Moreover, with the predictive controller, the voltages achieves very fast dynamic response and do not show any significant voltage overshoot and undershoot, which indicates the superiority of the controller.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117070893","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938245
Kamal Raj Singh, Ambalika Sharma, G. Singh
The domain of deep learning stimulates medical image analysis, which is a catalyst of scientific research and an essential element of healthcare. Since semantic segmentation techniques empower image processing and quantitative determination in various applications, designing a dedicated solution is challenging and heavily reliant on input data characteristics and hardware constraints. Cardiac magnetic resonance imaging segmentation provides three essential heart structures, left ventricle (LV) cavity, myocardium (MYO), and right ventricle (RV) cavity. In clinical applications, manual contouring is frequently utilized to perform semantic segmentation. A fully automated cardiac magnetic resonance image (CMRI) segmentation technique is becoming more desirable as deep learning-based frameworks advance. Motivated by the power of U-Net, residual network, and deep supervision, this paper proposes a Deep Residual U-Net to achieve better LV, MYO, and RV segmentation in short-axis CMRI. The model is formed with residual connections and has a similar layout to U-Net. It provides three advantages: First, residual connections make deep network training easier. Second, the network's rich skip connections enable feature propagation, allowing for network creation with lower complexity but more remarkable performance. Third, Deep supervision facilitates the loss computation at every feature dimension except at least two, empowering gradients to be implanted more deeply in the network and improving each layer's training in Deep Residual U-Net. Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset has been used to assess the segmentation efficiency of proposed model. The proposed approach significantly outperformed all other methods, evidencing its supremacy over recent state-of-the-art U-Net-based techniques.
{"title":"Cardiac Magnetic Resonance Imaging Segmentation using Ensemble of 2D and 3D Deep Residual U-Net","authors":"Kamal Raj Singh, Ambalika Sharma, G. Singh","doi":"10.1109/GlobConPT57482.2022.9938245","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938245","url":null,"abstract":"The domain of deep learning stimulates medical image analysis, which is a catalyst of scientific research and an essential element of healthcare. Since semantic segmentation techniques empower image processing and quantitative determination in various applications, designing a dedicated solution is challenging and heavily reliant on input data characteristics and hardware constraints. Cardiac magnetic resonance imaging segmentation provides three essential heart structures, left ventricle (LV) cavity, myocardium (MYO), and right ventricle (RV) cavity. In clinical applications, manual contouring is frequently utilized to perform semantic segmentation. A fully automated cardiac magnetic resonance image (CMRI) segmentation technique is becoming more desirable as deep learning-based frameworks advance. Motivated by the power of U-Net, residual network, and deep supervision, this paper proposes a Deep Residual U-Net to achieve better LV, MYO, and RV segmentation in short-axis CMRI. The model is formed with residual connections and has a similar layout to U-Net. It provides three advantages: First, residual connections make deep network training easier. Second, the network's rich skip connections enable feature propagation, allowing for network creation with lower complexity but more remarkable performance. Third, Deep supervision facilitates the loss computation at every feature dimension except at least two, empowering gradients to be implanted more deeply in the network and improving each layer's training in Deep Residual U-Net. Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset has been used to assess the segmentation efficiency of proposed model. The proposed approach significantly outperformed all other methods, evidencing its supremacy over recent state-of-the-art U-Net-based techniques.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115083715","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}
A novel Switched-Inductor Active Switched-Boost Inverter (SL-ASBI) is proposed in this paper by replacing two capacitors C2 and C3 in the switched-capacitor-inductor network (SCL-ASBI) with two diodes D4 and D5 keeping other parameters or elements remain same. The proposed topology provides same boost factor as that of SL-ZSI by a slighter numeral of apparatuses. Moreover, it provides less stress athwart the inductor and capacitor compared with a SCL-ASBI. The proposed inverter named as SL-ASBI, and examination of the projected inverter is carried out. The proposed SL-ASBI provides high boost factor /voltage gain at small duty ratio and at high modulation index to deliver better output wave shape. The theoretical examination is confirmed with the simulation outcomes. This projected topology also delivers unremitting input current, low capacitor stress besides little inrush current at start-up condition.
{"title":"Performance Analysis of Switched-Inductor Active Switched Boost Inverter","authors":"Vadthya Jagan, Chandrashekar Anupati, Shravan kumar Nallachervula, Hazrath Ali Shaik, Manasa Chilkamari","doi":"10.1109/GlobConPT57482.2022.9938366","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938366","url":null,"abstract":"A novel Switched-Inductor Active Switched-Boost Inverter (SL-ASBI) is proposed in this paper by replacing two capacitors C2 and C3 in the switched-capacitor-inductor network (SCL-ASBI) with two diodes D4 and D5 keeping other parameters or elements remain same. The proposed topology provides same boost factor as that of SL-ZSI by a slighter numeral of apparatuses. Moreover, it provides less stress athwart the inductor and capacitor compared with a SCL-ASBI. The proposed inverter named as SL-ASBI, and examination of the projected inverter is carried out. The proposed SL-ASBI provides high boost factor /voltage gain at small duty ratio and at high modulation index to deliver better output wave shape. The theoretical examination is confirmed with the simulation outcomes. This projected topology also delivers unremitting input current, low capacitor stress besides little inrush current at start-up condition.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091415","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938298
M. Darshan, S.R Raswanth, Priyanka Kumar
In recent times, the rise of Non Fungible Tokens has been inevitable. An NFT is a special kind of cryptographic token that represents the ownership of a unique piece of digital property. They are tamper-proof due to the use of distributed public ledger that records verified information across a network of computers. With the rise of crypto-trading, the NFT market segment has seen an accumulation in its trading volume in the capital market. There are various factors determining the price and sales of the NFTs and there is a need for meaningful insights from the data generated intermittently over time. With this as motivation, this proposed research work explores the factors that create an impact on the NFT market and in-depth data analysis with the help of brokerage firm data. This proposed work helps NFT enthusiasts would be able to derive the correlation between cryptocurrency market and NFT market.
{"title":"Data Analysis of Non Fungible Tokens (NFTs) Pricing using Brokerage Firm data","authors":"M. Darshan, S.R Raswanth, Priyanka Kumar","doi":"10.1109/GlobConPT57482.2022.9938298","DOIUrl":"https://doi.org/10.1109/GlobConPT57482.2022.9938298","url":null,"abstract":"In recent times, the rise of Non Fungible Tokens has been inevitable. An NFT is a special kind of cryptographic token that represents the ownership of a unique piece of digital property. They are tamper-proof due to the use of distributed public ledger that records verified information across a network of computers. With the rise of crypto-trading, the NFT market segment has seen an accumulation in its trading volume in the capital market. There are various factors determining the price and sales of the NFTs and there is a need for meaningful insights from the data generated intermittently over time. With this as motivation, this proposed research work explores the factors that create an impact on the NFT market and in-depth data analysis with the help of brokerage firm data. This proposed work helps NFT enthusiasts would be able to derive the correlation between cryptocurrency market and NFT market.","PeriodicalId":431406,"journal":{"name":"2022 IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115508949","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}
Pub Date : 2022-09-23DOI: 10.1109/GlobConPT57482.2022.9938228
N. P. Mannam, Sanju Kumar N T, Prasanth Kumar Duba, P. Rajalakshmi
Highly efficient propulsive mechanisms of aquatic swimming creatures could serve as inspiration for developing new propulsion methods where it exceeds the performance of present-day thrusters and propellers for ASVs, AUVs, and ROVs. The advantages of eco-friendly propulsion combined with a lesser wake could be advantageous for marine vehicles' stability and maneuvering. As a result, we need to improve our knowledge of fish or dolphin swimming hydrodynamics and their fluid-structure interaction to develop benchmark designs for new propulsion methods. Flapping foil thrusters for propulsion has sparked much interest in recent years. AUVs, ASVs, and ROVs vehicles could greatly benefit from this technology. In dolphin swimming kinematics, the flapping foil thruster is an essential component. This research aims to understand better the hydrodynamics and fluid-structure interaction of flapping foils subjected to heaving and pitching motions. In the present study, the bio-inspired flapping foil thrusters fitted with trailing edge flaps are studied experimentally using flow visualization techniques such as 2D particle image velocimetry (PIV). The time average vorticity contours and instantaneous velocity contours are presented in this study. The flapping foils with trailing edge flaps are immersed in a free stream of uniform flow speed varying from 5 to 10 cm/s. The operating Reynold number (Re) range is 500 to 4300. The Strouhal number range is 0.2 to 0.3. This study also investigated the effect of flapping foil without trailing edge flaps using 2D numerical simulations. By simulating the wake structure and its evolution, the present study aims to understand the vortex shedding mechanisms of flapping foil with or without trailing edge flaps, determining thrust and propulsive efficiency. The vortex shedding mechanisms for both the foils are presented and discussed in detail.
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