Pub Date : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673653
Femy Joseph, Ginnes. K. John, P. K
Solar photovoltaics array-based system is receiving wide attention because of it the abundant of solar energy. This paper deals with application of two switch buck-boost converter in solar PV array-based system for DC bus. The topologies of two switch buck boost converters allow a PV array to follow its maximum power point (MPP) regardless of irradiance, load, or temperature. Additionally, the buck boost converter may work in three modes: buck, boost, and buck boost. These converters give good efficiency even in light load periods. For making maximum out of the system adding Energy Sources System (ESS) makes it more reliability. Maximum output of PV array is obtained by using maximum power point tracking techniques that uses Perturb and Observe (P&O) algorithm. The whole system is evaluated in various solar irradiance using MATLAB/ SIMULINK platform.
{"title":"Solar Based Two Switch Buck Boost Converter with Battery as Energy Storage System for a Common DC Bus","authors":"Femy Joseph, Ginnes. K. John, P. K","doi":"10.1109/ICMSS53060.2021.9673653","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673653","url":null,"abstract":"Solar photovoltaics array-based system is receiving wide attention because of it the abundant of solar energy. This paper deals with application of two switch buck-boost converter in solar PV array-based system for DC bus. The topologies of two switch buck boost converters allow a PV array to follow its maximum power point (MPP) regardless of irradiance, load, or temperature. Additionally, the buck boost converter may work in three modes: buck, boost, and buck boost. These converters give good efficiency even in light load periods. For making maximum out of the system adding Energy Sources System (ESS) makes it more reliability. Maximum output of PV array is obtained by using maximum power point tracking techniques that uses Perturb and Observe (P&O) algorithm. The whole system is evaluated in various solar irradiance using MATLAB/ SIMULINK platform.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124154424","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673630
R. Divya, J. Dinesh Peter
Quantum technologies can provide innovative solutions to many complex problems, and thus quantum machine learning has taken a unique place in the world of computing. Quantum technology reaches an advanced level when the potential of quantum computing features is used for machine learning. Applying quantum computing features in traditional algorithms provides an exceptional parallel computing capability for solving complex problems. The essence of this paper is a comparative study of the basic concepts of quantum computing and their superior capabilities over classical computing. This article describes the application based algorithms such as QSVM, QPCA, and Q-KNN along with Grover's algorithm, which is the most popular and fundamental quantum machine learning algorithm. This study aims to understand various learning models that incorporate the advantages of computing into quantum circuits for enhancing classical machine learning functionalities.
{"title":"Quantum Machine Learning: A comprehensive review on optimization of machine learning algorithms","authors":"R. Divya, J. Dinesh Peter","doi":"10.1109/ICMSS53060.2021.9673630","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673630","url":null,"abstract":"Quantum technologies can provide innovative solutions to many complex problems, and thus quantum machine learning has taken a unique place in the world of computing. Quantum technology reaches an advanced level when the potential of quantum computing features is used for machine learning. Applying quantum computing features in traditional algorithms provides an exceptional parallel computing capability for solving complex problems. The essence of this paper is a comparative study of the basic concepts of quantum computing and their superior capabilities over classical computing. This article describes the application based algorithms such as QSVM, QPCA, and Q-KNN along with Grover's algorithm, which is the most popular and fundamental quantum machine learning algorithm. This study aims to understand various learning models that incorporate the advantages of computing into quantum circuits for enhancing classical machine learning functionalities.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"196 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116794287","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673597
Rt Moses, S. Natarajan, Malakreddy A Bharathi
To know the future is to know the past. The ability to properly estimate the future of a system is an elusive problem. Researchers have developed many tools to do just that, but a unified approach does not exist. Intertemporal causalities are main signages for predictions in computational finance. Here, since past value of a variable is highly correlated with the present and future of that variable, time series data analytics is much sought after modality for predictions. For a large temporal data set, time period bias is a very common sampling error, resulting in circumstance-specific unique observations only. Experts cannot extend such observations to a larger industry with wider problem spaces. In this paper, we propose a solution to fit any time series data, with an aim to eliminate the time period bias. In this work, we have created a system that meshes previously created systems such as ARIMA, ARMA, and AR. This helps to create a dynamic system that conforms to the specified time series data and modulates to create a specialized architecture for future prediction. We have taken test cases with varying hyperparameters and found a median accuracy of 94.95 % with a minimum delay in the training of 7 days and a median delay in training the model of 60 days.
{"title":"DIIT: A General Model for Time Series Projections, Proven on NIFTY Index Funds","authors":"Rt Moses, S. Natarajan, Malakreddy A Bharathi","doi":"10.1109/ICMSS53060.2021.9673597","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673597","url":null,"abstract":"To know the future is to know the past. The ability to properly estimate the future of a system is an elusive problem. Researchers have developed many tools to do just that, but a unified approach does not exist. Intertemporal causalities are main signages for predictions in computational finance. Here, since past value of a variable is highly correlated with the present and future of that variable, time series data analytics is much sought after modality for predictions. For a large temporal data set, time period bias is a very common sampling error, resulting in circumstance-specific unique observations only. Experts cannot extend such observations to a larger industry with wider problem spaces. In this paper, we propose a solution to fit any time series data, with an aim to eliminate the time period bias. In this work, we have created a system that meshes previously created systems such as ARIMA, ARMA, and AR. This helps to create a dynamic system that conforms to the specified time series data and modulates to create a specialized architecture for future prediction. We have taken test cases with varying hyperparameters and found a median accuracy of 94.95 % with a minimum delay in the training of 7 days and a median delay in training the model of 60 days.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116737415","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673609
M. Suman Menon, Anju George, N. Aswathy
Face recognition is one of the most functional research in present scenario, with many practical and commercial applications including identification, access control, forensics, medical care, human-computer interactions, security, etc. Face recognition technique is rapidly becoming the mainstay of state of the art technological security solution. One of the crucial applications of face recognition in the current scenario is linked with security. Identifying people from a crowd or a group of people require an exceptional algorithm. One of the most arduous tasks about the existing face recognition system is the processing or prediction time. The current systems focus on accuracy than speed, which leads to an increase in the detection time. There are several techniques in machine learning and deep learning. But deep learning is preferred more than machine learning for detection and recognition applications because of the large availability of data. An algorithm for fast real-time object detecting and recognizing application is required. YOLO (you only look once) is a single shot deep learning object detection algorithm. In this work, the working of the YOLO algorithm and implementing multiple face recognition using YOLO version 3 is explained. A custom dataset is created from taken from Kaggle and google. At the time of testing the model, a processing speed of 30 ms was obtained.
人脸识别是目前最具功能性的研究之一，在身份识别、访问控制、取证、医疗、人机交互、安全等领域有着广泛的实际和商业应用。人脸识别技术正迅速成为最先进的安全技术解决方案的支柱。在当前的场景中，人脸识别的关键应用之一与安全有关。从人群或一群人中识别人需要一种特殊的算法。现有的人脸识别系统最艰巨的任务之一是处理或预测时间。目前的系统更注重精度而不是速度，这导致了检测时间的增加。在机器学习和深度学习中有几种技术。但在检测和识别应用中，由于数据的大量可用性，深度学习比机器学习更受欢迎。需要一种快速实时的目标检测和识别算法。YOLO(你只看一次)是一个单镜头深度学习对象检测算法。本文介绍了YOLO算法的工作原理以及使用YOLO version 3实现多人脸识别。一个自定义数据集是从Kaggle和google中获取的。在对模型进行测试时，得到的处理速度为30 ms。
{"title":"Implementation of a Multitudinous Face Recognition using YOLO.V3","authors":"M. Suman Menon, Anju George, N. Aswathy","doi":"10.1109/ICMSS53060.2021.9673609","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673609","url":null,"abstract":"Face recognition is one of the most functional research in present scenario, with many practical and commercial applications including identification, access control, forensics, medical care, human-computer interactions, security, etc. Face recognition technique is rapidly becoming the mainstay of state of the art technological security solution. One of the crucial applications of face recognition in the current scenario is linked with security. Identifying people from a crowd or a group of people require an exceptional algorithm. One of the most arduous tasks about the existing face recognition system is the processing or prediction time. The current systems focus on accuracy than speed, which leads to an increase in the detection time. There are several techniques in machine learning and deep learning. But deep learning is preferred more than machine learning for detection and recognition applications because of the large availability of data. An algorithm for fast real-time object detecting and recognizing application is required. YOLO (you only look once) is a single shot deep learning object detection algorithm. In this work, the working of the YOLO algorithm and implementing multiple face recognition using YOLO version 3 is explained. A custom dataset is created from taken from Kaggle and google. At the time of testing the model, a processing speed of 30 ms was obtained.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123119293","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673592
R. Rajan, Joshua Antony, Riya Ann Joseph, Jijohn M. Thomas, Chandr Dhanush H, A. V
Listeners browse songs based on artist or genre, but a significant amount of queries are based on emotions like happy, sad, calm etc. and therefore, automatic music mood classification is gaining importance. People search for songs based on the emotions they are feeling or the emotion they hope to feel. Audio-based techniques can achieve satisfying results, but part of the semantic information of songs resides exclusively in the lyrics. In this paper, we present a study on the fusion approach of music mood classification. As both audio and lyrical information is complimentary, creating a hybrid model to classify music based on mood provides enhanced accuracy. Where a single song might fall under two different categories based on audio or lyrical information, a hybrid model helps us achieve more accurate results by merging both the information. In this work, we extracted features using librosa from audio, used TF-IDF for text, and experimented with the Bi-LSTM network. The performance evaluation is done on corpus consists of 776 songs. The multimodal approach achieved average precision, recall and F1-score of 0.66, 0.65 and 0.65 respectively.
{"title":"Audio-Mood Classification Using Acoustic-Textual Feature Fusion","authors":"R. Rajan, Joshua Antony, Riya Ann Joseph, Jijohn M. Thomas, Chandr Dhanush H, A. V","doi":"10.1109/ICMSS53060.2021.9673592","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673592","url":null,"abstract":"Listeners browse songs based on artist or genre, but a significant amount of queries are based on emotions like happy, sad, calm etc. and therefore, automatic music mood classification is gaining importance. People search for songs based on the emotions they are feeling or the emotion they hope to feel. Audio-based techniques can achieve satisfying results, but part of the semantic information of songs resides exclusively in the lyrics. In this paper, we present a study on the fusion approach of music mood classification. As both audio and lyrical information is complimentary, creating a hybrid model to classify music based on mood provides enhanced accuracy. Where a single song might fall under two different categories based on audio or lyrical information, a hybrid model helps us achieve more accurate results by merging both the information. In this work, we extracted features using librosa from audio, used TF-IDF for text, and experimented with the Bi-LSTM network. The performance evaluation is done on corpus consists of 776 songs. The multimodal approach achieved average precision, recall and F1-score of 0.66, 0.65 and 0.65 respectively.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126498105","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673632
S. Deepika, N. Nishanth, A. Mujeeb
Mobile Ad hoc Networks (MANETs) are decentralized wireless ad hoc networks comprising of self-organizing, self-configuring mobile nodes with constantly varying topology that serves as both the host as well as router. In order to communicate in such a mobile and diverse environment, the network makes use of routing protocols, so as to interconnect nodes which are dynamic and placed arbitrarily. The most predominantly used routing protocol is the Ad hoc On Demand Distance Vector (AODV) routing protocol. However, the constantly varying topology due to node mobility makes routing in MANET a hectic task. Link breakages and node failure in the network can lead to loss of network resources, which makes the optimal path selection between sender and receiver node quite necessary for reducing bandwidth usage, energy consumption and increasing the Quality of Service (QoS). Taking into consideration the routing issues in AODV, five recent AODV extension algorithms have been reviewed in this manuscript for finding their performances and short comings. The algorithms include an Enhanced-Ant-AODV, AODV based on TOPSIS and Fuzzy algorithm, Fungi network-based routing, Dynamic Power AODV (DP-AODV), and Dragon fly algorithm. In this review, some of the network performance parameters like the throughput, Packet Delivery Ratio (PDR), end-to-end delay, and routing overhead of each algorithm are analyzed and compared.
{"title":"An Assessment of Recent Advances in AODV Routing Protocol Path Optimization Algorithms for Mobile Ad hoc Networks","authors":"S. Deepika, N. Nishanth, A. Mujeeb","doi":"10.1109/ICMSS53060.2021.9673632","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673632","url":null,"abstract":"Mobile Ad hoc Networks (MANETs) are decentralized wireless ad hoc networks comprising of self-organizing, self-configuring mobile nodes with constantly varying topology that serves as both the host as well as router. In order to communicate in such a mobile and diverse environment, the network makes use of routing protocols, so as to interconnect nodes which are dynamic and placed arbitrarily. The most predominantly used routing protocol is the Ad hoc On Demand Distance Vector (AODV) routing protocol. However, the constantly varying topology due to node mobility makes routing in MANET a hectic task. Link breakages and node failure in the network can lead to loss of network resources, which makes the optimal path selection between sender and receiver node quite necessary for reducing bandwidth usage, energy consumption and increasing the Quality of Service (QoS). Taking into consideration the routing issues in AODV, five recent AODV extension algorithms have been reviewed in this manuscript for finding their performances and short comings. The algorithms include an Enhanced-Ant-AODV, AODV based on TOPSIS and Fuzzy algorithm, Fungi network-based routing, Dynamic Power AODV (DP-AODV), and Dragon fly algorithm. In this review, some of the network performance parameters like the throughput, Packet Delivery Ratio (PDR), end-to-end delay, and routing overhead of each algorithm are analyzed and compared.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133604008","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673638
Aswathy Santhosh, T. Saranya, S. Sundar, S. Natarajan
Deep Learning techniques have remarkably contributed to the advancement of medical image analysis by strengthening prediction accuracy, lead to proper drafting and diagnosis. Automated medical diagnosis using deep learning techniques help doctors, radiologists and clinical experts in the early detection and diagnosis of diseases. The conventional method for detecting the presence of lesions is more time consuming and labour-intensive. In this paper, we focus on reviewing various deep learning-based techniques used in the early identification of the diagnosis of brain tumors. These diagnosis tasks include feature extraction, segmentation, grading, classification, and prediction. This work carried out a detailed review of state-of-the-art innovations performed on each task related to brain tumor images. We summarized and analysed significant contributions over recent years and investigated their extensive advantages, limitations and dataset specification used in the experiments. Eventually, we addressed the ongoing challenges and future research propositions for practitioners in the domain.
{"title":"Deep Learning Techniques for Brain Tumor Diagnosis: A Review","authors":"Aswathy Santhosh, T. Saranya, S. Sundar, S. Natarajan","doi":"10.1109/ICMSS53060.2021.9673638","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673638","url":null,"abstract":"Deep Learning techniques have remarkably contributed to the advancement of medical image analysis by strengthening prediction accuracy, lead to proper drafting and diagnosis. Automated medical diagnosis using deep learning techniques help doctors, radiologists and clinical experts in the early detection and diagnosis of diseases. The conventional method for detecting the presence of lesions is more time consuming and labour-intensive. In this paper, we focus on reviewing various deep learning-based techniques used in the early identification of the diagnosis of brain tumors. These diagnosis tasks include feature extraction, segmentation, grading, classification, and prediction. This work carried out a detailed review of state-of-the-art innovations performed on each task related to brain tumor images. We summarized and analysed significant contributions over recent years and investigated their extensive advantages, limitations and dataset specification used in the experiments. Eventually, we addressed the ongoing challenges and future research propositions for practitioners in the domain.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128136041","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673626
Neha Saju, Neable Yohannan, Reshna Mamman, Nissan Kunju, Mohammad Abdul Shukoor, Sukomal Dev
The design of a wideband reflecting type linear-circular and linear-linear polarization converter in the THz frequency regime is described in depth in this work. The reflective polarizer unitcell seen here is made of a simple circular ring with two orthogonal cuts printed on top of a $text{Si} 0_{2}$ substrate which is terminated with the ground. Post simulation results show a linearly polarized $((x/y)$ incident wave converted to its cross $(y/x)$ component in two frequency bands (7.19-11.12 THz and 15.28-15.78 THz) after reflection. The reflected wave would also be circularly polarized in the frequency bands (5.77-6.38 THz and 12.40-14.01 THz). The proposed structure has a unitcell periodicity of 0.1846 $lambda_{mathrm{L}}$ and an effective thickness of 0.0685 $lambda_{mathrm{L}}$, where $lambda_{mathrm{L}}$ is the lowest broadband frequency. For linear to cross conversion, the proposed design has a stable reaction up to 45°, and for linear to circular conversion, it has a stable response up to 30°. Authors are convinced that the proposed geometry has several advantages like simple, compact, and angular stable. It is used in real-time applications like polarization beam-splitters and time-domain spectroscopy, where these conversions are the primary concern.
{"title":"A Simple Wideband Dual-Slotted Circular Ring Based Linear-Circular and Linear-Cross Reflective Type Polarizer for THz Regime","authors":"Neha Saju, Neable Yohannan, Reshna Mamman, Nissan Kunju, Mohammad Abdul Shukoor, Sukomal Dev","doi":"10.1109/ICMSS53060.2021.9673626","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673626","url":null,"abstract":"The design of a wideband reflecting type linear-circular and linear-linear polarization converter in the THz frequency regime is described in depth in this work. The reflective polarizer unitcell seen here is made of a simple circular ring with two orthogonal cuts printed on top of a $text{Si} 0_{2}$ substrate which is terminated with the ground. Post simulation results show a linearly polarized $((x/y)$ incident wave converted to its cross $(y/x)$ component in two frequency bands (7.19-11.12 THz and 15.28-15.78 THz) after reflection. The reflected wave would also be circularly polarized in the frequency bands (5.77-6.38 THz and 12.40-14.01 THz). The proposed structure has a unitcell periodicity of 0.1846 $lambda_{mathrm{L}}$ and an effective thickness of 0.0685 $lambda_{mathrm{L}}$, where $lambda_{mathrm{L}}$ is the lowest broadband frequency. For linear to cross conversion, the proposed design has a stable reaction up to 45°, and for linear to circular conversion, it has a stable response up to 30°. Authors are convinced that the proposed geometry has several advantages like simple, compact, and angular stable. It is used in real-time applications like polarization beam-splitters and time-domain spectroscopy, where these conversions are the primary concern.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126050133","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673610
S. Joseph, S. Karunan
Blockchain, the underlying technology behind Bit-coin, is an emerging technology in industry. Blockchain has the power to reform the existing business processes more democratic, transparent, secure, and efficient. Banking industries are the first movers that capitalize the disruptive potential of this technology. The indian banking system is one of the complex bank payment system in this world. The current infrastructure that is used by indian bank system is real time gross settlement system based and it follows a centralized architecture. Due to this centralized architecture the processing of transactions are slow and cum-bersome. It also causes large amount for security and recovery purposes. The real time gross settlement based system demands high need for security, resilience, and performance. Moving from traditional system to blockchain platform is not the prior concern but making a system that provide security, confidentiality, and decentralized money lending mechanism is the core idea. Here proposed a novel system that enable a decentralized Banking system and services based on Ethereum blockchain platform. The system support different services including money deposit, money transfer and loan checking etc. using the distributed ledger technology.
{"title":"A Blockchain Based Decentralized Transaction Settlement System in Banking Sector","authors":"S. Joseph, S. Karunan","doi":"10.1109/ICMSS53060.2021.9673610","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673610","url":null,"abstract":"Blockchain, the underlying technology behind Bit-coin, is an emerging technology in industry. Blockchain has the power to reform the existing business processes more democratic, transparent, secure, and efficient. Banking industries are the first movers that capitalize the disruptive potential of this technology. The indian banking system is one of the complex bank payment system in this world. The current infrastructure that is used by indian bank system is real time gross settlement system based and it follows a centralized architecture. Due to this centralized architecture the processing of transactions are slow and cum-bersome. It also causes large amount for security and recovery purposes. The real time gross settlement based system demands high need for security, resilience, and performance. Moving from traditional system to blockchain platform is not the prior concern but making a system that provide security, confidentiality, and decentralized money lending mechanism is the core idea. Here proposed a novel system that enable a decentralized Banking system and services based on Ethereum blockchain platform. The system support different services including money deposit, money transfer and loan checking etc. using the distributed ledger technology.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116024904","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 : 2021-11-18DOI: 10.1109/ICMSS53060.2021.9673641
R. Ram, S. Muhammed, S. M.
The design and deployment challenges for soft grippers include robustness, miniaturization, speed, and control. Bio mimicking micro robots and systems require simplicity, low power, lower computational requirement, and repeatability. The foremost choice for such systems is to shape memory alloy, due to its large strain and reduced size. This paper primarily deals with the study of the performance of a controller for accelerating the speed of the shape memory alloy (SMA) actuator. The temperature control in SMA is achieved using classical joule's heating method. Conventional temperature control in SMA is developed by using sensors like, thermocouple or thermal imaging sensors. But, for submillimetre diameter SMA actuators, this imposes a physical challenge by physically loading the miniature actuator. Here, a sensor-less temperature estimation method is developed by measuring the resistance variation of SMA during actuation. primarily this experiment is to make an actuator for which shall having some significant role in the field of Soft robotic gripper.
{"title":"Sensorless Heating Control of SMA","authors":"R. Ram, S. Muhammed, S. M.","doi":"10.1109/ICMSS53060.2021.9673641","DOIUrl":"https://doi.org/10.1109/ICMSS53060.2021.9673641","url":null,"abstract":"The design and deployment challenges for soft grippers include robustness, miniaturization, speed, and control. Bio mimicking micro robots and systems require simplicity, low power, lower computational requirement, and repeatability. The foremost choice for such systems is to shape memory alloy, due to its large strain and reduced size. This paper primarily deals with the study of the performance of a controller for accelerating the speed of the shape memory alloy (SMA) actuator. The temperature control in SMA is achieved using classical joule's heating method. Conventional temperature control in SMA is developed by using sensors like, thermocouple or thermal imaging sensors. But, for submillimetre diameter SMA actuators, this imposes a physical challenge by physically loading the miniature actuator. Here, a sensor-less temperature estimation method is developed by measuring the resistance variation of SMA during actuation. primarily this experiment is to make an actuator for which shall having some significant role in the field of Soft robotic gripper.","PeriodicalId":274597,"journal":{"name":"2021 Fourth International Conference on Microelectronics, Signals & Systems (ICMSS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115754466","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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