Pub Date : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243472
V. Prakasam, N. Reddy
This paper uses coaxial probe feed method to present, design, and simulate elliptical microstrip patch antenna at ISM band. This paper processes an innovative elliptical microstrip patch (MSPA) antenna at standard ISM frequency band ranges from 2.4 GHz to 2.5 GHz. The planned and simulated EMSPA operating frequency is 2.4 GHz to 2.5 GHz and 4.2, 4.4, 4.6 & 4.8 FR4 substrate, this selected frequency increases efficiency in terms of S11 and reasonable gain value. In this study, coaxial probes feed the proposed antenna fixed on an FR-4 substrate material which has 4.2, 4.4, 4.6 & 4.8 dielectric constant, substratum thickness is 6.6 mm. The intension of the proposed antenna is that to determine the higher gain, less S11 at different operating frequencies that are 2.35 GHz, 2.4 GHz, 2.45GHz and 2.5 GHz, which is the ISM band range. The high-performance systems such as rockets, ships, missiles and satellites use elliptical microstrip patch antennas. Antennas with optimal measurements of elliptical microstrip patches act as circularly polarized wave radiators. Various simulation antenna design software is available, such as FEKO, IE3D, CST, HFSS, Antenna Magus and MATLAB. Here, using MATLAB simulation software tool, the EMSPA is designed and simulated and also estimate the performance characteristics, such as s-parameter, vswr, EH fields, radiation pattern, current distribution, gain, elevation and azimuthal radiation pattern.
{"title":"Design and Simulation of Elliptical Micro strip Patch Antenna with Coaxial Probe Feeding for Satellites Applications Using Matlab","authors":"V. Prakasam, N. Reddy","doi":"10.1109/I-SMAC49090.2020.9243472","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243472","url":null,"abstract":"This paper uses coaxial probe feed method to present, design, and simulate elliptical microstrip patch antenna at ISM band. This paper processes an innovative elliptical microstrip patch (MSPA) antenna at standard ISM frequency band ranges from 2.4 GHz to 2.5 GHz. The planned and simulated EMSPA operating frequency is 2.4 GHz to 2.5 GHz and 4.2, 4.4, 4.6 & 4.8 FR4 substrate, this selected frequency increases efficiency in terms of S11 and reasonable gain value. In this study, coaxial probes feed the proposed antenna fixed on an FR-4 substrate material which has 4.2, 4.4, 4.6 & 4.8 dielectric constant, substratum thickness is 6.6 mm. The intension of the proposed antenna is that to determine the higher gain, less S11 at different operating frequencies that are 2.35 GHz, 2.4 GHz, 2.45GHz and 2.5 GHz, which is the ISM band range. The high-performance systems such as rockets, ships, missiles and satellites use elliptical microstrip patch antennas. Antennas with optimal measurements of elliptical microstrip patches act as circularly polarized wave radiators. Various simulation antenna design software is available, such as FEKO, IE3D, CST, HFSS, Antenna Magus and MATLAB. Here, using MATLAB simulation software tool, the EMSPA is designed and simulated and also estimate the performance characteristics, such as s-parameter, vswr, EH fields, radiation pattern, current distribution, gain, elevation and azimuthal radiation pattern.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114827329","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243512
Shwetha N, M. Priyatham
Digital communication has become an important part of our lives and technology has been undergoing advancements. The main two problems faced in digital communication is noise and inter-symbol interference (ISI). The IS I is induced due to channel characteristics, which is time-varying and unknown. Hence an adaptive channel equalizer is used to inverse the effect channel had on the signal to get back the initial information. There are many adaptive algorithms to update the coefficients of equalizers, evolutionary algorithms are used in this paper to do so. The two algorithms used before are particle swarm optimization (PSO) and conventional differential evolution (DE). The newest algorithm is the Evolutionary Programming Least Mean Square Algorithm (EPLMS) this gives a better solution faster.
{"title":"Performance Analysis of Self Adaptive Equalizers using EPLMS Algorithm","authors":"Shwetha N, M. Priyatham","doi":"10.1109/I-SMAC49090.2020.9243512","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243512","url":null,"abstract":"Digital communication has become an important part of our lives and technology has been undergoing advancements. The main two problems faced in digital communication is noise and inter-symbol interference (ISI). The IS I is induced due to channel characteristics, which is time-varying and unknown. Hence an adaptive channel equalizer is used to inverse the effect channel had on the signal to get back the initial information. There are many adaptive algorithms to update the coefficients of equalizers, evolutionary algorithms are used in this paper to do so. The two algorithms used before are particle swarm optimization (PSO) and conventional differential evolution (DE). The newest algorithm is the Evolutionary Programming Least Mean Square Algorithm (EPLMS) this gives a better solution faster.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121954224","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243531
Gundlapalle Raiesh, Boda Saroia, Manian Dhivya, A. B. Gurulakshmi
Histopathological examination of tissue models is basic for the conclusion and reviewing of colon malignancy. In any case, the technique is subjective and prompts imperative intra/bury spectator distinction in the examination as it predominantly relies upon the graphical evaluation of histopathologists. Thus, a tried and true PC supported technique, which can naturally group harmful and ordinary colon tests are required; however, automating this strategy is demanding because of the nearness of exceptions. In this paper, a productive technique for identifying colon disease from biopsy tests which comprise of four imperative stages. DB-SCAN estimation to distinguish colon tumor from biopsy tests is presented in this paper. In the proposed approach, from the outset, the colon biopsy tests are preprocessed using DB-SCAN configuration to make a set of redundant localities in which groups or clusters are formed. At that point, the exceptions inside the bunched areas are created as a tree structure in light of the choice tree in which the anomalies are hubs, and the connection between hubs are delivered based on data about exceptions. At that point, entropy-based exception score calculation will be done on every hub of the tree. The Information picks up technique is utilized to figure the score for the exceptions. At long last, score based grouping is accomplished to order the ordinary or harmful cells. Experimental trials exhibit, the proposed strategy has better outcomes contrasted to existing strategies. It furthermore acclaims that the proposed procedure is adequate for the colon tumor identification process. The proposed strategy is executed on Matlab working platform and the investigations exhibit that the proposed technique has high accomplished high grouping precision contrasted and different strategies.
{"title":"DB-Scan Algorithm based Colon Cancer Detection And Stratification Analysis","authors":"Gundlapalle Raiesh, Boda Saroia, Manian Dhivya, A. B. Gurulakshmi","doi":"10.1109/I-SMAC49090.2020.9243531","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243531","url":null,"abstract":"Histopathological examination of tissue models is basic for the conclusion and reviewing of colon malignancy. In any case, the technique is subjective and prompts imperative intra/bury spectator distinction in the examination as it predominantly relies upon the graphical evaluation of histopathologists. Thus, a tried and true PC supported technique, which can naturally group harmful and ordinary colon tests are required; however, automating this strategy is demanding because of the nearness of exceptions. In this paper, a productive technique for identifying colon disease from biopsy tests which comprise of four imperative stages. DB-SCAN estimation to distinguish colon tumor from biopsy tests is presented in this paper. In the proposed approach, from the outset, the colon biopsy tests are preprocessed using DB-SCAN configuration to make a set of redundant localities in which groups or clusters are formed. At that point, the exceptions inside the bunched areas are created as a tree structure in light of the choice tree in which the anomalies are hubs, and the connection between hubs are delivered based on data about exceptions. At that point, entropy-based exception score calculation will be done on every hub of the tree. The Information picks up technique is utilized to figure the score for the exceptions. At long last, score based grouping is accomplished to order the ordinary or harmful cells. Experimental trials exhibit, the proposed strategy has better outcomes contrasted to existing strategies. It furthermore acclaims that the proposed procedure is adequate for the colon tumor identification process. The proposed strategy is executed on Matlab working platform and the investigations exhibit that the proposed technique has high accomplished high grouping precision contrasted and different strategies.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125385971","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243412
J. K. Solomon Doss, S. Kamalakkannan
In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details.
{"title":"IoT System Accomplishment using BlockChain in Validating and Data Security with Cloud","authors":"J. K. Solomon Doss, S. Kamalakkannan","doi":"10.1109/I-SMAC49090.2020.9243412","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243412","url":null,"abstract":"In a block channel IoT system, sensitive details can be leaked by means of the proof of work or address check, as data or application Validation data is applied on the blockchain. In this, the zero-knowledge evidence is applied to a smart metering system to show how to improve the anonymity of the blockchain for privacy safety without disclosing information as a public key. Within this article, a blockchain has been implemented to deter security risks such as data counterfeiting by utilizing intelligent meters. Zero-Knowledge Proof, an anonymity blockchain technology, has been implemented through block inquiry to prevent threats to security like personal information infringement. It was suggested that intelligent contracts would be used to avoid falsification of intelligent meter data and abuse of personal details.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"156 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125914070","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243334
Vaibhav Jain, Dhruv Chandel, Piyush Garg, D. Vishwakarma
Depression is the leading global disability, and unipolar (as opposed to bipolar) depression is the 10th leading cause of early death, as stated by the World Health Organization (WHO) in 2015. The study aims to build an approach for depression and impaired mental health analysis from social media platforms. Although for Depression analysis and cure. Psyscologists preferred over machines because they are manipulative and precautionary to Human emotions to a greater extent, Machine Learning has an added advantage. It has no emotions; it studies patterns, not face or beauty or other factors. It studies a wide variety of data and then trains to give better predictions. Although it is not 100% reliable nor are the doctors. Moreover, in countries like India where people don't treat Depression as a Chronic Illness or don't even consider it as an illness of any sort, embedding Machine Learning Depression Detection Algorithms in Social Media combined with recommendation systems to treat a Human Mind positively, still being unnoticeable is a Great Boon to humanity The study is assisted by data collected from users after obtaining their consent and applying data preprocessing techniques. Several machine learning is used to analyze the data in the best way possible. A VAPID Technique is developed that performs far better than a classic feed-forward neural network. This study aims to develop a correlation between features and depressed people to observe a continuous pattern. Moreover, the aim is to conclude that social media can be a new exceptional methodology for analyzing depression and analyzing indirect patterns, improving many lives.
{"title":"Depression and Impaired Mental Health Analysis from Social Media Platforms using Predictive Modelling Techniques","authors":"Vaibhav Jain, Dhruv Chandel, Piyush Garg, D. Vishwakarma","doi":"10.1109/I-SMAC49090.2020.9243334","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243334","url":null,"abstract":"Depression is the leading global disability, and unipolar (as opposed to bipolar) depression is the 10th leading cause of early death, as stated by the World Health Organization (WHO) in 2015. The study aims to build an approach for depression and impaired mental health analysis from social media platforms. Although for Depression analysis and cure. Psyscologists preferred over machines because they are manipulative and precautionary to Human emotions to a greater extent, Machine Learning has an added advantage. It has no emotions; it studies patterns, not face or beauty or other factors. It studies a wide variety of data and then trains to give better predictions. Although it is not 100% reliable nor are the doctors. Moreover, in countries like India where people don't treat Depression as a Chronic Illness or don't even consider it as an illness of any sort, embedding Machine Learning Depression Detection Algorithms in Social Media combined with recommendation systems to treat a Human Mind positively, still being unnoticeable is a Great Boon to humanity The study is assisted by data collected from users after obtaining their consent and applying data preprocessing techniques. Several machine learning is used to analyze the data in the best way possible. A VAPID Technique is developed that performs far better than a classic feed-forward neural network. This study aims to develop a correlation between features and depressed people to observe a continuous pattern. Moreover, the aim is to conclude that social media can be a new exceptional methodology for analyzing depression and analyzing indirect patterns, improving many lives.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130109443","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243419
P. Kanehanadevi, D. Selvapandian, Laxmi Raja, R. Dhanapal
Cloud provides several benefits in e-health care. Based on current trends, the E-healthcare database could be linked to cloud services. This work provides an idea of combining a structure for monitoring electronic-health services based on the cloud environment. With this, we are planning to adapt it to distributed computing. This framework has been enhanced in order to provide a variety of health services. The whole framework of the E-Healthcare Database Maintenance System covers the consumer side and the application side and Cloud. In order to improve safety in the e-health system, the biometric confirmation system is added in order to avoid non-criminal situations and to forget about the password situation. In addition to this framework, we add a security module to enhance the safety and privacy of patients. Our proposed framework improves the security, privacy, time, and cost of access to health information.
{"title":"Cloud-based Protection and Performance Improvement in the E-Health Management Framework","authors":"P. Kanehanadevi, D. Selvapandian, Laxmi Raja, R. Dhanapal","doi":"10.1109/I-SMAC49090.2020.9243419","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243419","url":null,"abstract":"Cloud provides several benefits in e-health care. Based on current trends, the E-healthcare database could be linked to cloud services. This work provides an idea of combining a structure for monitoring electronic-health services based on the cloud environment. With this, we are planning to adapt it to distributed computing. This framework has been enhanced in order to provide a variety of health services. The whole framework of the E-Healthcare Database Maintenance System covers the consumer side and the application side and Cloud. In order to improve safety in the e-health system, the biometric confirmation system is added in order to avoid non-criminal situations and to forget about the password situation. In addition to this framework, we add a security module to enhance the safety and privacy of patients. Our proposed framework improves the security, privacy, time, and cost of access to health information.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124497550","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243309
Kayalvizhi Jayavel, Kanagaraj Venusamy, L. G
Internet of Things (IoT) test beds are widely used by developers predominantly. Off late, Test beds are being used by data analysts, academicians, industrial persons and hardware ardent. The real purpose of test beds, is to achieve accurate testing results, mimicking the real time environment to the extent possible which is otherwise not possible to reproduce using simulators. As predicted by many industrial giants IoT based devices will reach the scale of billions by 2015. The applications and opportunities they create will also be innumerable. This has created a huge demand for such testing grounds, because a system deployed without proper testing may be vulnerable and sometimes disastrous. Thus our research aims to explore the qualities of test beds, the services they offer and how to enhance the performance of test beds. Our test bed framework is designed and developed with open-source boards to achieved heterogeneity, reusability, interoperability and scalability. This framework would like to be addressed as a utility, with “X” as service: data, sensor client, actuator client, and platform. To achieve this, APIs which is platform and language independent has been developed and provides third-party developer support. The APIs developed have shown considerable improvement in terms of data transfer rate, database upload and retrieval, and user responsiveness. Thus, our framework is capable of offering services through our API. And have demonstrated with the help of conditional probability techniques enhancement in performance and reusability, visualized the same in terms of graphs and datasets.
{"title":"Design and Implementation of IoT Testbed with Improved Reliability using Conditional Probability Techniques","authors":"Kayalvizhi Jayavel, Kanagaraj Venusamy, L. G","doi":"10.1109/I-SMAC49090.2020.9243309","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243309","url":null,"abstract":"Internet of Things (IoT) test beds are widely used by developers predominantly. Off late, Test beds are being used by data analysts, academicians, industrial persons and hardware ardent. The real purpose of test beds, is to achieve accurate testing results, mimicking the real time environment to the extent possible which is otherwise not possible to reproduce using simulators. As predicted by many industrial giants IoT based devices will reach the scale of billions by 2015. The applications and opportunities they create will also be innumerable. This has created a huge demand for such testing grounds, because a system deployed without proper testing may be vulnerable and sometimes disastrous. Thus our research aims to explore the qualities of test beds, the services they offer and how to enhance the performance of test beds. Our test bed framework is designed and developed with open-source boards to achieved heterogeneity, reusability, interoperability and scalability. This framework would like to be addressed as a utility, with “X” as service: data, sensor client, actuator client, and platform. To achieve this, APIs which is platform and language independent has been developed and provides third-party developer support. The APIs developed have shown considerable improvement in terms of data transfer rate, database upload and retrieval, and user responsiveness. Thus, our framework is capable of offering services through our API. And have demonstrated with the help of conditional probability techniques enhancement in performance and reusability, visualized the same in terms of graphs and datasets.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"274 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122153410","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243473
M. Hans, Manoj Kumar Nigam, Maheshwari D. Mirajkar, Brijesh Patel
The advanced control method for electric reactive power compensation with the help of electronics components is binary current control method. This method allows a sufficient number of compensating branches to establish a fine and precise control of reactive power in electrical system. This method consists of Thyristor binary switched capacitor (TBSC) and Thyristor binary switched reactor (TBSR), which are based on the series of Thyristor switched capacitor (TSC) and Thyristor controlled reactor (TCR). The bank of TSC, TCR arranged in binary form i.e. split bank in multiple of two. For harmonic elimination use transient free switching of TBSC, TBSR In this paper three topologies are explained 1) TBSC 2) TBSR 3) TBSC-TBSR for reactive power compensation of dynamic load. In the third topology excessive KVAR given by TBSC is absorbed by TBSR. The simulation results show that the proposed topologies can achieve reactive power compensation.
{"title":"Simulation based reactive power compensation by using TBSC/TBSR for dynamic load","authors":"M. Hans, Manoj Kumar Nigam, Maheshwari D. Mirajkar, Brijesh Patel","doi":"10.1109/I-SMAC49090.2020.9243473","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243473","url":null,"abstract":"The advanced control method for electric reactive power compensation with the help of electronics components is binary current control method. This method allows a sufficient number of compensating branches to establish a fine and precise control of reactive power in electrical system. This method consists of Thyristor binary switched capacitor (TBSC) and Thyristor binary switched reactor (TBSR), which are based on the series of Thyristor switched capacitor (TSC) and Thyristor controlled reactor (TCR). The bank of TSC, TCR arranged in binary form i.e. split bank in multiple of two. For harmonic elimination use transient free switching of TBSC, TBSR In this paper three topologies are explained 1) TBSC 2) TBSR 3) TBSC-TBSR for reactive power compensation of dynamic load. In the third topology excessive KVAR given by TBSC is absorbed by TBSR. The simulation results show that the proposed topologies can achieve reactive power compensation.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"17 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120821047","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243545
Praveen Kumar Sadineni
Today we are living in a digital world where most of the activities performed are online. Fraud transactions are ever growing since the growth of ecommerce applications. Millions of transactions are happening around every second everyday giving us the benefit of enjoying financial services through credit and debit cards. Fraud transactions are allowing illegal users to misuse the money of genuine users causing them financial loss. Accessibility of credit card transactions data, techniques used by the frauds, identifying scams in the bulk data which is getting produced very quickly, imbalanced data are some of the major challenges involved in detecting fraudulent credit card transactions. Hence, we need powerful techniques to identify fraudulent transactions. The current paper deals with various machine learning techniques such as Artificial Neural Network (ANN), Decision Trees, Support Vector Machine (SVM), Logistic Regression and Random Forest to detect fraudulent transactions. Performance analysis of these techniques is done using Accuracy, Precision and False alarm rate metrics. Dataset used to carry out the experiment is taken from Kaggle data repository. The experiment shows that Radom Forest could achieve an accuracy of 99.21%, Decision Tree 98.47%. Logistic Regression 95.55%, SVM 95.16% and ANN 99.92%.
今天，我们生活在一个数字世界，大多数活动都是在网上进行的。随着电子商务应用的发展，欺诈交易越来越多。每时每刻都有数以百万计的交易发生，这让我们可以通过信用卡和借记卡享受金融服务。欺诈交易允许非法用户滥用真正用户的钱，给他们造成经济损失。信用卡交易数据的可访问性、欺诈者使用的技术、在快速生成的大量数据中识别骗局、不平衡数据是检测欺诈性信用卡交易所涉及的一些主要挑战。因此，我们需要强大的技术来识别欺诈性交易。本文涉及各种机器学习技术，如人工神经网络(ANN)，决策树，支持向量机(SVM)，逻辑回归和随机森林来检测欺诈交易。这些技术的性能分析是使用准确度、精度和虚警率指标来完成的。用于实验的数据集取自Kaggle数据库。实验表明，随机森林的准确率为99.21%，决策树的准确率为98.47%。Logistic回归95.55%，SVM 95.16%， ANN 99.92%。
{"title":"Detection of Fraudulent Transactions in Credit Card using Machine Learning Algorithms","authors":"Praveen Kumar Sadineni","doi":"10.1109/I-SMAC49090.2020.9243545","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243545","url":null,"abstract":"Today we are living in a digital world where most of the activities performed are online. Fraud transactions are ever growing since the growth of ecommerce applications. Millions of transactions are happening around every second everyday giving us the benefit of enjoying financial services through credit and debit cards. Fraud transactions are allowing illegal users to misuse the money of genuine users causing them financial loss. Accessibility of credit card transactions data, techniques used by the frauds, identifying scams in the bulk data which is getting produced very quickly, imbalanced data are some of the major challenges involved in detecting fraudulent credit card transactions. Hence, we need powerful techniques to identify fraudulent transactions. The current paper deals with various machine learning techniques such as Artificial Neural Network (ANN), Decision Trees, Support Vector Machine (SVM), Logistic Regression and Random Forest to detect fraudulent transactions. Performance analysis of these techniques is done using Accuracy, Precision and False alarm rate metrics. Dataset used to carry out the experiment is taken from Kaggle data repository. The experiment shows that Radom Forest could achieve an accuracy of 99.21%, Decision Tree 98.47%. Logistic Regression 95.55%, SVM 95.16% and ANN 99.92%.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120941111","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 : 2020-10-07DOI: 10.1109/I-SMAC49090.2020.9243328
J. Divya, S. Shivagami
With the expansion of distributed computing, security of sensitive client information is emerging as a significant challenge. This paper proposes a secured cloud engineering with an equipment security module that separates cloud client information from conceivably malignant special areas or cloud chairmen. Further, the equipment security module gives basic security usefulness within a safely disconnected execution condition with just limited interfaces presented to weak administration frameworks or then again to cloud directors. Such limitation forestalls cloud directors from influencing the security of visitor instances [7]. The proposed building not simply makes preparations for wide attack vectors yet furthermore achieves a hardware security module [12]. This paper talks about the equipment and programming of the proposed cloud design along with its security and presents its exhibition results.
{"title":"A study of Secure cryptographic based Hardware security module in a cloud environment","authors":"J. Divya, S. Shivagami","doi":"10.1109/I-SMAC49090.2020.9243328","DOIUrl":"https://doi.org/10.1109/I-SMAC49090.2020.9243328","url":null,"abstract":"With the expansion of distributed computing, security of sensitive client information is emerging as a significant challenge. This paper proposes a secured cloud engineering with an equipment security module that separates cloud client information from conceivably malignant special areas or cloud chairmen. Further, the equipment security module gives basic security usefulness within a safely disconnected execution condition with just limited interfaces presented to weak administration frameworks or then again to cloud directors. Such limitation forestalls cloud directors from influencing the security of visitor instances [7]. The proposed building not simply makes preparations for wide attack vectors yet furthermore achieves a hardware security module [12]. This paper talks about the equipment and programming of the proposed cloud design along with its security and presents its exhibition results.","PeriodicalId":432766,"journal":{"name":"2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)","volume":"71 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120941556","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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