Pub Date : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974539
Law Kumar Singh, Pooja, H. Garg
Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is the disease where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from retinal fundus images. The proposed method suggests automatic detection the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach of fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 97.75% 92.50% and 95.00% when tested on DRIONS, DRIVE and STARE on publicly available databases of retinal fundus images.
{"title":"Detection of Glaucoma in Retinal Fundus Images Using Fast Fuzzy C means clustering approach","authors":"Law Kumar Singh, Pooja, H. Garg","doi":"10.1109/ICCCIS48478.2019.8974539","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974539","url":null,"abstract":"Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is the disease where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from retinal fundus images. The proposed method suggests automatic detection the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach of fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 97.75% 92.50% and 95.00% when tested on DRIONS, DRIVE and STARE on publicly available databases of retinal fundus images.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061828","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974493
Maliha Khan, Sudeshna Chakraborty, Rani Astya, Shaveta Khepra
Face detection and picture or video recognition is a popular subject of research on biometrics. Face recognition in a real-time setting has an exciting area and a rapidly growing challenge. Framework for the use of face recognition application authentication. This proposes the PCA (Principal Component Analysis) facial recognition system. The key component analysis (PCA) is a statistical method under the broad heading of factor analysis. The aim of the PCA is to reduce the large amount of data storage to the size of the feature space that is required to represent the data economically. The wide 1-D pixel vector made of the 2-D face picture in compact main elements of the space function is designed for facial recognition by the PCA. This is called a projection of self-space. The proper space is determined with the identification of the covariance matrix’s own vectors, which are centered on a collection of fingerprint images. I build a camera-based real-time face recognition system and set an algorithm by developing programming on OpenCV, Haar Cascade, Eigenface, Fisher Face, LBPH, and Python.
{"title":"Face Detection and Recognition Using OpenCV","authors":"Maliha Khan, Sudeshna Chakraborty, Rani Astya, Shaveta Khepra","doi":"10.1109/ICCCIS48478.2019.8974493","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974493","url":null,"abstract":"Face detection and picture or video recognition is a popular subject of research on biometrics. Face recognition in a real-time setting has an exciting area and a rapidly growing challenge. Framework for the use of face recognition application authentication. This proposes the PCA (Principal Component Analysis) facial recognition system. The key component analysis (PCA) is a statistical method under the broad heading of factor analysis. The aim of the PCA is to reduce the large amount of data storage to the size of the feature space that is required to represent the data economically. The wide 1-D pixel vector made of the 2-D face picture in compact main elements of the space function is designed for facial recognition by the PCA. This is called a projection of self-space. The proper space is determined with the identification of the covariance matrix’s own vectors, which are centered on a collection of fingerprint images. I build a camera-based real-time face recognition system and set an algorithm by developing programming on OpenCV, Haar Cascade, Eigenface, Fisher Face, LBPH, and Python.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115382905","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974517
Abhishek Badholia, Vijayant Verma, S. Kashyap
The modern communication lies with the Wireless Network Systems (WNS). This paper studies the three popular WNS protocols i.e. WEP, WAP and WAP2. The improved version of WEP, WAP and WAP2 is presented in this paper. The proposed algorithm performs better than the existed. The new WEP, WAP and WAP2 are based on the algebraic, statistics and logarithmic methods. Thus the improved WEP, WAP and WAP2 perform better as per the standards of security and efficiency.
{"title":"Wep, Wap and Wap2 Wireless Network Security Protocol: A Compact Algorithm : (Wireless Network Security Protocol)","authors":"Abhishek Badholia, Vijayant Verma, S. Kashyap","doi":"10.1109/ICCCIS48478.2019.8974517","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974517","url":null,"abstract":"The modern communication lies with the Wireless Network Systems (WNS). This paper studies the three popular WNS protocols i.e. WEP, WAP and WAP2. The improved version of WEP, WAP and WAP2 is presented in this paper. The proposed algorithm performs better than the existed. The new WEP, WAP and WAP2 are based on the algebraic, statistics and logarithmic methods. Thus the improved WEP, WAP and WAP2 perform better as per the standards of security and efficiency.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114816557","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974516
Zaheeruddin, Hina Gupta
The sustainable development of traffic conditions in the urban area is hindered by the improper management of traffic. The characteristics of traffic congestion in the Urban areas vary under the influence of different conditions, such as different day and time of week, count of vehicles on road, causality on road and the parking of vehicles etc. It is necessary to set up the relationships between traffic congestion patterns and those influencing factors, when we conduct macroscopic analysis on the causes of traffic congestion. The bottleneck situation arising out of congestion has made the commuting of Emergency Vehicles(EV) a tedious and tough job. The rationale of this work is to pay heed to the way the Emergency Vehicles commute in order to decline their travel time and provide a clear path. The paper probes into several key issues or key enablers that need to be managed properly in order to have an organised traffic. The work has been carried out on the basis of the previous studies and the discernment of the proficient involved in management of traffic. In this work, a technique named, Interpretive Structure Modelling(ISM) has been employed, for comprehending the hierarchical and contextual affiliation structure amongst the various key enablers.
{"title":"Key enablers influencing the realization of green corridor for the Emergency Vehicles in India using ISM approach","authors":"Zaheeruddin, Hina Gupta","doi":"10.1109/ICCCIS48478.2019.8974516","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974516","url":null,"abstract":"The sustainable development of traffic conditions in the urban area is hindered by the improper management of traffic. The characteristics of traffic congestion in the Urban areas vary under the influence of different conditions, such as different day and time of week, count of vehicles on road, causality on road and the parking of vehicles etc. It is necessary to set up the relationships between traffic congestion patterns and those influencing factors, when we conduct macroscopic analysis on the causes of traffic congestion. The bottleneck situation arising out of congestion has made the commuting of Emergency Vehicles(EV) a tedious and tough job. The rationale of this work is to pay heed to the way the Emergency Vehicles commute in order to decline their travel time and provide a clear path. The paper probes into several key issues or key enablers that need to be managed properly in order to have an organised traffic. The work has been carried out on the basis of the previous studies and the discernment of the proficient involved in management of traffic. In this work, a technique named, Interpretive Structure Modelling(ISM) has been employed, for comprehending the hierarchical and contextual affiliation structure amongst the various key enablers.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117197343","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974551
A. Rana, Ayodeji Olalekan Salau, Swati Gupta, S. Arora
With the advent of rapid developments, large number of heterogeneous devices is able to connect with the help of IOT technology. Although IOT possess very complex architecture because of connectivity of variety of devices and services in the system. In this paper, a brief concept of urban IOT system is presented which are designed to support smart city and advanced communication technologies. Hence a comprehensive survey of architecture, technologies, and computational frameworks is provided for a smart IOT. It also discusses the major vulnerabilities and challenges faced by IOT and also present how machine learning is applied to IOT. Hence smart city is considered as the use case and it explains how various techniques are applied to data in order to extract great results with good efficiency.
{"title":"Machine learning methods for IoT and their Future Applications","authors":"A. Rana, Ayodeji Olalekan Salau, Swati Gupta, S. Arora","doi":"10.1109/ICCCIS48478.2019.8974551","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974551","url":null,"abstract":"With the advent of rapid developments, large number of heterogeneous devices is able to connect with the help of IOT technology. Although IOT possess very complex architecture because of connectivity of variety of devices and services in the system. In this paper, a brief concept of urban IOT system is presented which are designed to support smart city and advanced communication technologies. Hence a comprehensive survey of architecture, technologies, and computational frameworks is provided for a smart IOT. It also discusses the major vulnerabilities and challenges faced by IOT and also present how machine learning is applied to IOT. Hence smart city is considered as the use case and it explains how various techniques are applied to data in order to extract great results with good efficiency.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"2001 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131797195","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974504
Keshav Gupta, G. S. Walia, K. Sharma
Biometric systems are need of the day because of their various advantages over traditional authentication systems. Multimodal Biometric systems combine information from multiple sources to reach a final decision. Score level fusion combines outcomes of individual classffiers to make a final decision. However, most of the biometric systems suffer from the issue of score confliction of individual classifiers. To resolve this issue, we have proposed a novel optimized score level fusion using Grasshopper optimization where the performance optimization of individual classffiers is performed and a concurrent solution is achieved by means of proportional conflict redistribution rules. The system does not require any classifier training and exhibits high performance. The proposed system is robust against the dynamic environment and exhibits high reliability.
{"title":"Multimodal Biometric System using Grasshopper Optimization","authors":"Keshav Gupta, G. S. Walia, K. Sharma","doi":"10.1109/ICCCIS48478.2019.8974504","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974504","url":null,"abstract":"Biometric systems are need of the day because of their various advantages over traditional authentication systems. Multimodal Biometric systems combine information from multiple sources to reach a final decision. Score level fusion combines outcomes of individual classffiers to make a final decision. However, most of the biometric systems suffer from the issue of score confliction of individual classifiers. To resolve this issue, we have proposed a novel optimized score level fusion using Grasshopper optimization where the performance optimization of individual classffiers is performed and a concurrent solution is achieved by means of proportional conflict redistribution rules. The system does not require any classifier training and exhibits high performance. The proposed system is robust against the dynamic environment and exhibits high reliability.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126219878","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974463
Reena Panwar, S. M.
Cloud is a collection of heterogeneouscomputing resources that are presented to the users on the payment basis. Cloud and the associated resources are dynamic in nature. The provisioning of resources in such dynamic environment is one of the critical issues in the cloud. Various Quality of Service (QoS) parameters contribute to the provisioning of appropriate resources in the cloud. A right proportion of resource provisioning is necessary to improve the performance of the system. To mention, energy wastage and cost increase due to over-provisioning, while, under-provisioning may seem to effect Service Level Agreements (SLA) and Service Quality (QoS). Hence, the virtual resources should be allocated accordingly to fulfil the current dynamic demand of various applications. This paper presents a deeper survey on the various resource allocation frameworks for service-based cloud applications.
{"title":"Autonomic Resource Allocation Frameworks for Service-based Cloud Applications: A Survey","authors":"Reena Panwar, S. M.","doi":"10.1109/ICCCIS48478.2019.8974463","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974463","url":null,"abstract":"Cloud is a collection of heterogeneouscomputing resources that are presented to the users on the payment basis. Cloud and the associated resources are dynamic in nature. The provisioning of resources in such dynamic environment is one of the critical issues in the cloud. Various Quality of Service (QoS) parameters contribute to the provisioning of appropriate resources in the cloud. A right proportion of resource provisioning is necessary to improve the performance of the system. To mention, energy wastage and cost increase due to over-provisioning, while, under-provisioning may seem to effect Service Level Agreements (SLA) and Service Quality (QoS). Hence, the virtual resources should be allocated accordingly to fulfil the current dynamic demand of various applications. This paper presents a deeper survey on the various resource allocation frameworks for service-based cloud applications.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129180603","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974503
Dev Arora, S. Gautham, H. Gupta, B. Bhushan
The emerging blockchain technology helps in the decentralization of transactions, where every participant network verifies and validates the transaction making it immutable. With the rapid expansion of the technology, transactional data which is stored and validated is also increasing. The blockchain technology came into prominence largely due to the bitcoin and the security aspects of the technology. This technology is comparatively fast, secure and efficient. This paper discusses the generalized overview, different algorithms to reach consensus, system workflows and various security aspects of handling, transacting and storing data. This paper also throws light Smart Contracts and their applications.
{"title":"Blockchain-based Security Solutions to Preserve Data Privacy And Integrity","authors":"Dev Arora, S. Gautham, H. Gupta, B. Bhushan","doi":"10.1109/ICCCIS48478.2019.8974503","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974503","url":null,"abstract":"The emerging blockchain technology helps in the decentralization of transactions, where every participant network verifies and validates the transaction making it immutable. With the rapid expansion of the technology, transactional data which is stored and validated is also increasing. The blockchain technology came into prominence largely due to the bitcoin and the security aspects of the technology. This technology is comparatively fast, secure and efficient. This paper discusses the generalized overview, different algorithms to reach consensus, system workflows and various security aspects of handling, transacting and storing data. This paper also throws light Smart Contracts and their applications.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127308232","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974502
S. Borana, S. K. Yadav, S. Parihar
Hyperspectral Images are continuous narrow spectral bands provides a wealth of information which can be used in different applications. Advance developments in hyperspectral remote sensing technology since two decade have opened new opportunity to explore innovative ways to study vegetation species. In this research work, ground-based AISA Vis-NIR hyper spectral image system of 240 bands, wavelength range from 390 to 960 nm with 2.5 nm spectral resolution and 1cm spatial resolution at a distance of 10m was used for classification of prominent vegetation species (Cactus, Neem and Babool). Machine learning supervised classification algorithms are used to classifying the Hyperspectral data. In supervised classification, four methods have been used viz. Spectral Angle Mapper (SAM), Minimum Distance (MD), Support Vector Machine (SVM) and Spectral Information Divergence (SID) Classifier. Environment of Visualize Images (ENVI) software is used for processing and analysis of hyperspectral images for classification of vegetation species in Jodhpur study area. Accuracy assessments were also carried out for classified output images and estimate the performance of a classifier. The overall accuracy for SVM classification algorithm is best (81.2%) when 237 hyperspectral bands were used and SAM classification algorithm has provided a better overall accuracy (76.6%) when maximum noise function (MNF) 11 bands were used. This research demonstrated the efficient use of contiguous fine bands of Hyperspectral data in discrimination and classification of vegetation species.
高光谱图像是连续的窄光谱带，提供了丰富的信息，可用于不同的应用。近二十年来，高光谱遥感技术的发展为探索创新的植被物种研究方法提供了新的机遇。本研究利用240个波段，波长390 ~ 960 nm，光谱分辨率2.5 nm，空间分辨率1cm，距离10m的AISA可见光-近红外高光谱图像系统，对仙人掌、印楝和巴布尔等突出植被进行分类。采用机器学习监督分类算法对高光谱数据进行分类。在监督分类中，使用了四种方法，即光谱角映射器(SAM)、最小距离(MD)、支持向量机(SVM)和光谱信息发散(SID)分类器。利用环境可视化图像软件(Environment of visualimages, ENVI)对焦特布尔研究区植被种类分类的高光谱图像进行处理和分析。准确度评估也进行了分类输出图像和估计一个分类器的性能。当使用237个高光谱波段时，SVM分类算法的总体准确率最高(81.2%)，而当使用最大噪声函数(MNF) 11个波段时，SAM分类算法的总体准确率最高(76.6%)。本研究证明了连续精细波段高光谱数据在植被种类识别和分类中的有效利用。
{"title":"Hyperspectral Data Analysis for Arid Vegetation Species : Smart & Sustainable Growth","authors":"S. Borana, S. K. Yadav, S. Parihar","doi":"10.1109/ICCCIS48478.2019.8974502","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974502","url":null,"abstract":"Hyperspectral Images are continuous narrow spectral bands provides a wealth of information which can be used in different applications. Advance developments in hyperspectral remote sensing technology since two decade have opened new opportunity to explore innovative ways to study vegetation species. In this research work, ground-based AISA Vis-NIR hyper spectral image system of 240 bands, wavelength range from 390 to 960 nm with 2.5 nm spectral resolution and 1cm spatial resolution at a distance of 10m was used for classification of prominent vegetation species (Cactus, Neem and Babool). Machine learning supervised classification algorithms are used to classifying the Hyperspectral data. In supervised classification, four methods have been used viz. Spectral Angle Mapper (SAM), Minimum Distance (MD), Support Vector Machine (SVM) and Spectral Information Divergence (SID) Classifier. Environment of Visualize Images (ENVI) software is used for processing and analysis of hyperspectral images for classification of vegetation species in Jodhpur study area. Accuracy assessments were also carried out for classified output images and estimate the performance of a classifier. The overall accuracy for SVM classification algorithm is best (81.2%) when 237 hyperspectral bands were used and SAM classification algorithm has provided a better overall accuracy (76.6%) when maximum noise function (MNF) 11 bands were used. This research demonstrated the efficient use of contiguous fine bands of Hyperspectral data in discrimination and classification of vegetation species.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126079215","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974467
D. Agrawal, S. Maheshwari
This paper present a Current Mode Instrumentation Amplifier (CMIA) that employs a low voltage Extra-X Current Conveyor (EX-CCII), operable at ±0.75V. The proposed circuit utilizes one EX-CCII, and a grounded resistor. The circuit provides the low input impedance of 105 Ω and high output impedance of 0.31 MΩ which is favourable for the cascading without additional buffers. The non-ideal and parasitic effects on the circuit performance are being carried out. The theoretical predictions are well supported through verification results by using the PSPICE program.
{"title":"Low Voltage Current Mode Instrumentation Amplifier","authors":"D. Agrawal, S. Maheshwari","doi":"10.1109/ICCCIS48478.2019.8974467","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974467","url":null,"abstract":"This paper present a Current Mode Instrumentation Amplifier (CMIA) that employs a low voltage Extra-X Current Conveyor (EX-CCII), operable at ±0.75V. The proposed circuit utilizes one EX-CCII, and a grounded resistor. The circuit provides the low input impedance of 105 Ω and high output impedance of 0.31 MΩ which is favourable for the cascading without additional buffers. The non-ideal and parasitic effects on the circuit performance are being carried out. The theoretical predictions are well supported through verification results by using the PSPICE program.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115017482","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：