Pub Date : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170498
T. Ilakkia, M. Vetrivel, M..Nancy Jeniffer, P. Velmurugan, L. G. Prasad
The Optimal Power Flow (OPF) plays a major role in proper planning and operation of a power system. Its basic objective is minimization of fuel cost. Similarly, the placement and size of the compensators have a significant impact on the OPF problems. Numerous heuristic optimization approaches has been implemented to tackle the OPF and placement of FACTS devices. In this present work, a novel HHO based topology achieves multi objective OPE by integrating the STATCOM. The power flow analysis is utilized to identify the STATCOM’s location. The algorithm is very simple to implement. The size of STATCOM, voltage profile improvement, voltage stability improvement and loss reduction are considered as the performance indicators. This proposed topology is implemented on the IEEE 30 bus system. The superiority of this proposed topology can be verified by comparing the obtained results with the other existing topologies.
{"title":"An efficient Optimal Sizing model for STATCOM using Harris Hawk Optimization in Power System","authors":"T. Ilakkia, M. Vetrivel, M..Nancy Jeniffer, P. Velmurugan, L. G. Prasad","doi":"10.1109/IConSCEPT57958.2023.10170498","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170498","url":null,"abstract":"The Optimal Power Flow (OPF) plays a major role in proper planning and operation of a power system. Its basic objective is minimization of fuel cost. Similarly, the placement and size of the compensators have a significant impact on the OPF problems. Numerous heuristic optimization approaches has been implemented to tackle the OPF and placement of FACTS devices. In this present work, a novel HHO based topology achieves multi objective OPE by integrating the STATCOM. The power flow analysis is utilized to identify the STATCOM’s location. The algorithm is very simple to implement. The size of STATCOM, voltage profile improvement, voltage stability improvement and loss reduction are considered as the performance indicators. This proposed topology is implemented on the IEEE 30 bus system. The superiority of this proposed topology can be verified by comparing the obtained results with the other existing topologies.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125800406","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170733
Pon Pradeep Kumar Murugesan, Velmurugan P G Sivabalin, Suresh Madhan Nanjan, T. S. Jayaraman
Beyond 5G (B5G) communication systems refer to the sixth generation (6G) of mobile communication which is expected to offer speeds up to 100 times faster than the current 5G communication systems. In addition, 6G communication systems are expected to use more advanced spectrum such as Terahertz (THz) or millimeter Wave (mmWave) communication, allowing for much higher data rates. Holographic communication involving Large Intelligent surfaces (LIS) is an optimal and efficient way of communication for 6G or B5G. It ensures effective and precise communication of data from transmitter to receiver. It is considered to be the ultimate form of wireless communication, using large antennas operating at THz frequencies in the Fresnel region (radiating near-field). In this paper, the region or boundary for large size antenna surfaces are explored. In comparison to traditional MIMO (Multiple Input Multiple Output) systems, it is possible to exploit Degrees of Freedom (DoF) values greater than 1 even in strong Line of Sight (LoS) channel conditions, resulting in a notable increase in spatial capacity, particularly when operating at THz or mmWaves range. The Prolate Spheroidal Wave Function (PSWF) and Ultra-Wideband (UWB) Pulse Shapes are used to generate Orthogonal Modes. The time-limited and broad bandwidth characteristics of the orthogonal signal waveforms make the PSWF a great asset in the design of UWB pulse-shapes. The use of Legendre polynomials yields modes that are mutually Orthogonal. By utilizing Holographic communication systems, the capacity of a channel can be enhanced when compared to classical communication systems.
{"title":"Orthogonal Modes using Prolate Spheroidal Wave Function in Holographic Communication Systems","authors":"Pon Pradeep Kumar Murugesan, Velmurugan P G Sivabalin, Suresh Madhan Nanjan, T. S. Jayaraman","doi":"10.1109/IConSCEPT57958.2023.10170733","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170733","url":null,"abstract":"Beyond 5G (B5G) communication systems refer to the sixth generation (6G) of mobile communication which is expected to offer speeds up to 100 times faster than the current 5G communication systems. In addition, 6G communication systems are expected to use more advanced spectrum such as Terahertz (THz) or millimeter Wave (mmWave) communication, allowing for much higher data rates. Holographic communication involving Large Intelligent surfaces (LIS) is an optimal and efficient way of communication for 6G or B5G. It ensures effective and precise communication of data from transmitter to receiver. It is considered to be the ultimate form of wireless communication, using large antennas operating at THz frequencies in the Fresnel region (radiating near-field). In this paper, the region or boundary for large size antenna surfaces are explored. In comparison to traditional MIMO (Multiple Input Multiple Output) systems, it is possible to exploit Degrees of Freedom (DoF) values greater than 1 even in strong Line of Sight (LoS) channel conditions, resulting in a notable increase in spatial capacity, particularly when operating at THz or mmWaves range. The Prolate Spheroidal Wave Function (PSWF) and Ultra-Wideband (UWB) Pulse Shapes are used to generate Orthogonal Modes. The time-limited and broad bandwidth characteristics of the orthogonal signal waveforms make the PSWF a great asset in the design of UWB pulse-shapes. The use of Legendre polynomials yields modes that are mutually Orthogonal. By utilizing Holographic communication systems, the capacity of a channel can be enhanced when compared to classical communication systems.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126340740","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170245
G. Themozhi, I. Jayasukumari
Filters with a low profile are in great demand. Traditionally, band pass filters are distributed. Because to its simplicity, adaptability, and low cost, the Substrate Integrated Waveguide (SIW) is a strong contender for mm-wave technology. The majority of the benefits of traditional metallic waveguide, including full shielding, low loss, high quality factor, and high power handling capacity, are also maintained by this technology. At millimeter wave frequencies about 60 GHz, SIW has drawn a lot of interest. The design of a conformal array antenna based on a substrate integrated waveguide (SIW) is recommended in this paper. The recommended antenna is used specifically in Wireless Personal Area Network (WPAN) for short range communication and functions as a flexible antenna with minimal thickness. A conformal design has a 2*9 and 2*4 array with 26 slot antennas that operate at frequencies between 1 and 6 GHz. Lower Bending Loss, utilised in either on-body or off-body applications, Flexible communication, and improved design efficiency are the project’s key benefits. Our research offers several feeding methods to enhance performance. The performance of the recommended design has been shown together with the design rule. The Advanced Design System (ADS) 2020 software is used to analyse the simulation findings, including the resonant frequency, return loss and radiation patterns of the proposed antenna.
{"title":"Design and Analysis of Conformal Array Antenna","authors":"G. Themozhi, I. Jayasukumari","doi":"10.1109/IConSCEPT57958.2023.10170245","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170245","url":null,"abstract":"Filters with a low profile are in great demand. Traditionally, band pass filters are distributed. Because to its simplicity, adaptability, and low cost, the Substrate Integrated Waveguide (SIW) is a strong contender for mm-wave technology. The majority of the benefits of traditional metallic waveguide, including full shielding, low loss, high quality factor, and high power handling capacity, are also maintained by this technology. At millimeter wave frequencies about 60 GHz, SIW has drawn a lot of interest. The design of a conformal array antenna based on a substrate integrated waveguide (SIW) is recommended in this paper. The recommended antenna is used specifically in Wireless Personal Area Network (WPAN) for short range communication and functions as a flexible antenna with minimal thickness. A conformal design has a 2*9 and 2*4 array with 26 slot antennas that operate at frequencies between 1 and 6 GHz. Lower Bending Loss, utilised in either on-body or off-body applications, Flexible communication, and improved design efficiency are the project’s key benefits. Our research offers several feeding methods to enhance performance. The performance of the recommended design has been shown together with the design rule. The Advanced Design System (ADS) 2020 software is used to analyse the simulation findings, including the resonant frequency, return loss and radiation patterns of the proposed antenna.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"31 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120987968","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170665
A. Kumar, S. Balanethiram
Cardiovascular diseases (CVDs) are a significant cause of human death and impose a considerable economic burden on society. Early detection and prevention of CVDs can be achieved through home monitoring systems, utilizing wearable sensors to continuously record Electrocardiogram (ECG) signals from the human heart over extended periods of time. However, the design of a wearable biomedical sensor presents challenges, including motion artifact due to body movements and the need for low power consumption. In this research article, we propose an Analog Front End (AFE) that is DC coupled and consists of an FDDA-based Instrumentation Amplifier (IA) and a Programmable Gain Amplifier (PGA) with an AC coupled input stage. Our proposed AFE possesses the required characteristics for effective CVD detection, including high input impedance, low noise, high Common Mode Rejection Ratio (CMRR), and ultralow power. To address the challenge of motion artifact, we increase the AFE input impedance, while keeping the circuit as simple as possible for low power consumption. The proposed AFE is implemented in $0.18 mu mathrm{m}$ CMOS process with a supply voltage of 1.8V provides an excellent gain of 76dB, CMRR of around 127dB with less output noise voltage and high input impedance. Our AFE, when incorporated into a complete biomedical sensor, is capable of accurately detecting ECG signals in the range of 1-2 millivolt peak to peak, enabling the determination of heart rate or beats per minute.
心血管疾病是人类死亡的一个重要原因，给社会造成了相当大的经济负担。通过家庭监测系统，可以实现心血管疾病的早期检测和预防，该系统利用可穿戴传感器长时间连续记录人类心脏的心电图(ECG)信号。然而，可穿戴生物医学传感器的设计面临挑战，包括由于身体运动而产生的运动伪影和对低功耗的需求。在这篇研究文章中，我们提出了一个模拟前端(AFE)，它是直流耦合的，由一个基于fdma的仪表放大器(IA)和一个带有交流耦合输入级的可编程增益放大器(PGA)组成。我们提出的AFE具有有效CVD检测所需的特性，包括高输入阻抗、低噪声、高共模抑制比(CMRR)和超低功耗。为了解决运动伪影的挑战，我们增加了AFE输入阻抗，同时保持电路尽可能简单以实现低功耗。该AFE采用$0.18 mu maththrm {m}$ CMOS工艺实现，电源电压为1.8V，增益为76dB, CMRR约为127dB，输出噪声电压小，输入阻抗高。我们的AFE，当整合到一个完整的生物医学传感器中时，能够准确地检测1-2毫伏的峰值范围内的ECG信号，从而确定心率或每分钟跳动次数。
{"title":"DC-Coupled Fully Differential Difference Amplifier-Based Analog Front-End Design for Wearable ECG Sensors","authors":"A. Kumar, S. Balanethiram","doi":"10.1109/IConSCEPT57958.2023.10170665","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170665","url":null,"abstract":"Cardiovascular diseases (CVDs) are a significant cause of human death and impose a considerable economic burden on society. Early detection and prevention of CVDs can be achieved through home monitoring systems, utilizing wearable sensors to continuously record Electrocardiogram (ECG) signals from the human heart over extended periods of time. However, the design of a wearable biomedical sensor presents challenges, including motion artifact due to body movements and the need for low power consumption. In this research article, we propose an Analog Front End (AFE) that is DC coupled and consists of an FDDA-based Instrumentation Amplifier (IA) and a Programmable Gain Amplifier (PGA) with an AC coupled input stage. Our proposed AFE possesses the required characteristics for effective CVD detection, including high input impedance, low noise, high Common Mode Rejection Ratio (CMRR), and ultralow power. To address the challenge of motion artifact, we increase the AFE input impedance, while keeping the circuit as simple as possible for low power consumption. The proposed AFE is implemented in $0.18 mu mathrm{m}$ CMOS process with a supply voltage of 1.8V provides an excellent gain of 76dB, CMRR of around 127dB with less output noise voltage and high input impedance. Our AFE, when incorporated into a complete biomedical sensor, is capable of accurately detecting ECG signals in the range of 1-2 millivolt peak to peak, enabling the determination of heart rate or beats per minute.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121296256","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 biological indicator that foretells women’s general health is the menstrual cycle. For this project, the objective is to create a femtech platform where women can open up about their menstrual health. With features like a cycle tracker, PCOD detection, product awareness, Knowledge chapters, and doctor consultation, MonAmie presents an approach to raising general awareness about menstruation. This paper contains comparisons among Machine Learning algorithms which are used in the product, as well as the findings of MonAmie are discussed.
{"title":"Comprehensive FemTech Solution for Feminine Health","authors":"Nupur Jeswani, Nidhi Jain, Aarushi Sharma, Sukanya Roychowdhury","doi":"10.1109/IConSCEPT57958.2023.10170571","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170571","url":null,"abstract":"A biological indicator that foretells women’s general health is the menstrual cycle. For this project, the objective is to create a femtech platform where women can open up about their menstrual health. With features like a cycle tracker, PCOD detection, product awareness, Knowledge chapters, and doctor consultation, MonAmie presents an approach to raising general awareness about menstruation. This paper contains comparisons among Machine Learning algorithms which are used in the product, as well as the findings of MonAmie are discussed.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115197372","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170575
R. R. Rubia Gandhi, S. Makanth, V.P. Abhi, R. Amritha, M. Harish
The power generation from solar photovoltaic is variable in nature, and may contain unacceptable fluctuations so in current use the renewable energy is stored in the battery or super capacitors to use it later but it requires high maintenance charge. The main idea for the proposed work is to regulate the renewable power during the fluctuation to give uninterrupted power supply. The continuous monitoring of power generation from solar is carried out by machine learning model using KNN algorithm and simultaneously the load consuming values are again sent to machine learned model to classify the switching status of regulator circuit. Using Thonny software, the dataset is fed to the model and all these AI process is done in Python Platform. Hardware implementation for the same is used with 1200 W solar panel and for the load variation, three LED’s are used. Panel when exposed to sunlight, solar power is utilized using BUCK converter and when no light falls on the panel, the SMPS supply the LED switching from solar power to DC rectifier.
{"title":"An Improved Voltage Regulation in DC Smart Grid Using Machine Learning","authors":"R. R. Rubia Gandhi, S. Makanth, V.P. Abhi, R. Amritha, M. Harish","doi":"10.1109/IConSCEPT57958.2023.10170575","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170575","url":null,"abstract":"The power generation from solar photovoltaic is variable in nature, and may contain unacceptable fluctuations so in current use the renewable energy is stored in the battery or super capacitors to use it later but it requires high maintenance charge. The main idea for the proposed work is to regulate the renewable power during the fluctuation to give uninterrupted power supply. The continuous monitoring of power generation from solar is carried out by machine learning model using KNN algorithm and simultaneously the load consuming values are again sent to machine learned model to classify the switching status of regulator circuit. Using Thonny software, the dataset is fed to the model and all these AI process is done in Python Platform. Hardware implementation for the same is used with 1200 W solar panel and for the load variation, three LED’s are used. Panel when exposed to sunlight, solar power is utilized using BUCK converter and when no light falls on the panel, the SMPS supply the LED switching from solar power to DC rectifier.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125356962","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170448
Ashraf A. Shanaq, M. Zohdy
This paper investigates a lithium-ion battery’s charging and discharging behavior using the RC equivalent circuit model. The study aims to analyze the relationship between the battery’s open circuit voltage and model parameters and to evaluate the accuracy of the model’s predictions of the battery’s performance. The research seeks to optimize the battery’s performance by improving our understanding of its behavior and identifying ways to enhance its charging and discharging characteristics.
{"title":"Optimizing Lithium-ion Battery Performance with RC Equivalent Circuit Model Analysis","authors":"Ashraf A. Shanaq, M. Zohdy","doi":"10.1109/IConSCEPT57958.2023.10170448","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170448","url":null,"abstract":"This paper investigates a lithium-ion battery’s charging and discharging behavior using the RC equivalent circuit model. The study aims to analyze the relationship between the battery’s open circuit voltage and model parameters and to evaluate the accuracy of the model’s predictions of the battery’s performance. The research seeks to optimize the battery’s performance by improving our understanding of its behavior and identifying ways to enhance its charging and discharging characteristics.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126535595","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10169946
S. M. Roomi, S. Suvetha, P. Maheswari, R. Suganya, K. Priya
Knee Osteoarthritis (KOA) is a common joint degeneration identified by joint stiffness, pain, and functional disability. Physical symptoms, medical histories, and other joint screening techniques like radiography, MRIs, and CT scans are commonly taken into account while evaluating it. The traditional approaches, however, are quite subjective, which makes it difficult to detect early sickness progression. We propose, a machine-learning approach to automatically classify the severity of KOA using MRI images. Mask RCNN segments the knee’s upper and lower joints. The cartilage area is then the Region of Interest (ROI), which is acquired via morphological techniques. The radon transform is used to extract the dominating features from ROI, and the K Nearest Neighbor (KNN) classifier is used to categorize them. Comparing the experimental findings of the suggested technique to those of other machine learning classifiers and state-of-the-art methods, the proposed method outperformed them all with a classification accuracy of 88%. The results of the studies show that the suggested method aids surgeons in early diagnosis and minimizes problems associated with KOA.
{"title":"Radon Feature Based Osteoarthritis Severity Assessment","authors":"S. M. Roomi, S. Suvetha, P. Maheswari, R. Suganya, K. Priya","doi":"10.1109/IConSCEPT57958.2023.10169946","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10169946","url":null,"abstract":"Knee Osteoarthritis (KOA) is a common joint degeneration identified by joint stiffness, pain, and functional disability. Physical symptoms, medical histories, and other joint screening techniques like radiography, MRIs, and CT scans are commonly taken into account while evaluating it. The traditional approaches, however, are quite subjective, which makes it difficult to detect early sickness progression. We propose, a machine-learning approach to automatically classify the severity of KOA using MRI images. Mask RCNN segments the knee’s upper and lower joints. The cartilage area is then the Region of Interest (ROI), which is acquired via morphological techniques. The radon transform is used to extract the dominating features from ROI, and the K Nearest Neighbor (KNN) classifier is used to categorize them. Comparing the experimental findings of the suggested technique to those of other machine learning classifiers and state-of-the-art methods, the proposed method outperformed them all with a classification accuracy of 88%. The results of the studies show that the suggested method aids surgeons in early diagnosis and minimizes problems associated with KOA.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116983699","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170712
R. Maurya, Sarsij Tripathi
The unprecedented progress in the domain of quantum computing in the last few years has influenced researchers around the globe to solve multitudes of problems in this promising computing technology. This power of the quantum computer has allowed multitudes of computationally hard problems to be sped up exponentially over their classical counterparts. Along with such power, another promising application of quantum computing has been found in image processing and machine learning. Researches in both quantum image processing and quantum machine learning are still in their infancy but promise exceptional power over its classical counterparts. In this thesis, neural networks will be trained to determine parameters for various parametric quantum circuits to perform important classification tasks, such as image classification. But for image classification, features from the images must also be extracted and epresented in terms of qubits, requiring convolutional layers tailored for quantum techniques. This thesis aims to find good quantum convolutional neural network architectures for image classification with higher accuracy. This is still challenging due to increased cost and error with a higher number of qubits within a system. This thesis is expected to be important in the future direction of the research of quantum CNN.
{"title":"Image Classification using Quantum Convolutional Neural Network","authors":"R. Maurya, Sarsij Tripathi","doi":"10.1109/IConSCEPT57958.2023.10170712","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170712","url":null,"abstract":"The unprecedented progress in the domain of quantum computing in the last few years has influenced researchers around the globe to solve multitudes of problems in this promising computing technology. This power of the quantum computer has allowed multitudes of computationally hard problems to be sped up exponentially over their classical counterparts. Along with such power, another promising application of quantum computing has been found in image processing and machine learning. Researches in both quantum image processing and quantum machine learning are still in their infancy but promise exceptional power over its classical counterparts. In this thesis, neural networks will be trained to determine parameters for various parametric quantum circuits to perform important classification tasks, such as image classification. But for image classification, features from the images must also be extracted and epresented in terms of qubits, requiring convolutional layers tailored for quantum techniques. This thesis aims to find good quantum convolutional neural network architectures for image classification with higher accuracy. This is still challenging due to increased cost and error with a higher number of qubits within a system. This thesis is expected to be important in the future direction of the research of quantum CNN.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114298396","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 : 2023-05-25DOI: 10.1109/IConSCEPT57958.2023.10170120
S. Priya, R. M. Shereef
The detection of islanding is very important for the safe operation of distributed generators (DG) and microgrids (MG). A multiple DG microgrid based islanding detection scheme is proposed. Every DG’s harmonics and unbalanced voltage characteristics at the PCC are extracted using the discrete wavelet transform (DWT). The Random Forest (RF) classifier is used for classification. An IEEE-13 bus system with a solar PV array and a diesel generator as DGs modelled in SIMULINK is taken as the test system for the proposed method. The performance of the proposed method is tested by generating various scenarios like changing loads, introducing faults, and switching capacitors in the system. The results show the method is promising in terms of accuracy and speed.
{"title":"Intelligent Islanding Detection Scheme for Multiple DG Microgrids using Random Forest Classifier","authors":"S. Priya, R. M. Shereef","doi":"10.1109/IConSCEPT57958.2023.10170120","DOIUrl":"https://doi.org/10.1109/IConSCEPT57958.2023.10170120","url":null,"abstract":"The detection of islanding is very important for the safe operation of distributed generators (DG) and microgrids (MG). A multiple DG microgrid based islanding detection scheme is proposed. Every DG’s harmonics and unbalanced voltage characteristics at the PCC are extracted using the discrete wavelet transform (DWT). The Random Forest (RF) classifier is used for classification. An IEEE-13 bus system with a solar PV array and a diesel generator as DGs modelled in SIMULINK is taken as the test system for the proposed method. The performance of the proposed method is tested by generating various scenarios like changing loads, introducing faults, and switching capacitors in the system. The results show the method is promising in terms of accuracy and speed.","PeriodicalId":240167,"journal":{"name":"2023 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121818419","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}
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