2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)最新文献_第9页

Velocity Estimation Method Considering Doppler Effect and PSO Based Algorithm for Satellites Constellation IRNSS and GPS 考虑多普勒效应和基于粒子群算法的卫星星座IRNSS和GPS速度估计方法

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198579

G. Jyothi, B. Dhanraj, J. Pavanija, G. Kiran Kumar, A. Bose, Pratibha Verma

{"title":"Velocity Estimation Method Considering Doppler Effect and PSO Based Algorithm for Satellites Constellation IRNSS and GPS","authors":"G. Jyothi, B. Dhanraj, J. Pavanija, G. Kiran Kumar, A. Bose, Pratibha Verma","doi":"10.1109/CONECCT50063.2020.9198579","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198579","url":null,"abstract":"In this work, a method for velocity estimation of the user is done using a GPS-IRNSS/NavIC/ SBAS (IGS) receiver. With the help of the receiver in a moving vehicle, dynamic data is logged continuously in IRNSS/ NavIC+GPS hybrid operation to get receiver’s coordinates, Geometric dilution of precision (GDOP) and receiver’s velocity. The logged values of receiver’s coordinate contain errors, which is minimized first considering Satellite Selection Algorithm (SSA) based on GDOP values and then by applying PSO based algorithm to reduce Doppler shift effect and receiver’s clock offset. After improvement of dynamic receiver’s coordinates for each observation, velocity of receiver is calculated. Results show that velocity obtained using this estimation technique is more accurate in comparison to the velocity information provided by the IGS receiver. This finds major applications in real time vehicle tracking for various applications. In addition, atmospheric delays are expressed here in terms of Doppler shift.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131910526","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}

引用次数: 0

Forecasting Interannual Space-based CO2 Concentration using Geostatistical Mapping Approach 利用地统计填图方法预测年际天基二氧化碳浓度

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198511

Shrutilipi Bhattacharjee, Katharina Dill, Jia Chen

{"title":"Forecasting Interannual Space-based CO2 Concentration using Geostatistical Mapping Approach","authors":"Shrutilipi Bhattacharjee, Katharina Dill, Jia Chen","doi":"10.1109/CONECCT50063.2020.9198511","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198511","url":null,"abstract":"NASAs Orbiting Carbon Observatory-2 (OCO-2) is a recent satellite mission primarily aimed at measuring the column concentration of the carbon dioxide (CO2) in the atmosphere. The atmospheric CO2 concentration is measured as continuous swaths of the parallelogram footprints which are available as the Level-2 samples with a swath width of 10.3 km approximately. The temporal frequency of the retrieval at one place is 16 days approximately. This work attempts to forecast the OCO-2 samples at an interannual time scale from the available past samples at the nearby locations using geostatistical spatiotemporal kriging-based mapping approaches. This forecasting is needed to understand the future seasonal behavior of CO2 beforehand. For the validation, we have used the XCO2 swaths of OCO-2 in a study region from 2015 - 2019 and foretasted in the year of 2018 and 2019. One of the variant approaches found to produce 1.52 ppm root mean square error (RMSE), which is a good result with limited samples. This approach is capable of spatio-temporal prediction and forecasting of other products of OCO-2 and might be improved further by considering correlated auxiliary variables in the study region.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131793053","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}

引用次数: 2

GPU Assist using DSP Pre-processor GPU辅助使用DSP预处理器

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198650

Mihir Mody, H. Hariyani, Anand Balagopalakrishnan, Jason Jones, Ajay Jayaraj, Y. Prithvishankar

{"title":"GPU Assist using DSP Pre-processor","authors":"Mihir Mody, H. Hariyani, Anand Balagopalakrishnan, Jason Jones, Ajay Jayaraj, Y. Prithvishankar","doi":"10.1109/CONECCT50063.2020.9198650","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198650","url":null,"abstract":"There is an ever increasing need for higher GPU performance to render sophisticated User Interface, latest high end 3D games and general purpose compute (GPGPU) applications. GPU SW programming models such as OpenGL have evolved over decades to cater to the unique mixed pipeline 3D GPU architectures. Due to the sticky nature of GPU SW programming model, leveraging other HW blocks to enhance graphics performance has been a most challenging task for SW architects. System designers have usually responded to the GFLOPS demand by increasing the GPU HW specifications. This paper proposes enhancing GPU performance by leveraging DSP transparently in background without impacting GPU software programming model. The proposed solution consists of multiple novel techniques namely ability to offload vertex shader to DSP, 3 stage pipelined execution and ability to re-use GPU internal pipeline. The proposed solution is prototyped in Jacinoto6 Platform from Texas Instruments. The default GPU spec performance is increased by up-to 41% by leveraging dual core C66x DSP in Jacinto6 Platform using proposed solution for different use-cases. The proposed solution is fully transparent to application software stack. In addition, the solution is directly applicable to any GPU + DSP architecture making it attractive approach for cost optimized solutions.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128327215","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}

引用次数: 2

OntoDisco: Improving Web Service Discovery by Hybridization of Ontology Focused Concept Clustering and Interface Semantics OntoDisco:基于本体的概念聚类和接口语义的杂交改进Web服务发现

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198428

P. N, G. Deepak, Ayush Kumar, T. J, V. R.

{"title":"OntoDisco: Improving Web Service Discovery by Hybridization of Ontology Focused Concept Clustering and Interface Semantics","authors":"P. N, G. Deepak, Ayush Kumar, T. J, V. R.","doi":"10.1109/CONECCT50063.2020.9198428","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198428","url":null,"abstract":"Web services can be regarded as the most vital constituent of the World Wide Web as each of the web services is associated with an important role. With the paradigm shift toward Service Oriented Architecture, Service computing has become quite predominant across the globe. Web service discovery is not just important but also crucial and cumbersome. This paper proposes a new web service discovery approach that is semantics aware. This approach helps to extract the underlying semantics and enables users to utilize web services. The strategy focuses on the creation of a web database comprising of dataset crawled from well-known registry sites. A word-level semantics is applied using clustering based on the NPMI value. The library creation happens based on the semantic similarity values. An ontology for the principal classes of web services is modeled to facilitate clustering based on the initial aggregation of the data and the concepts. Finally, a web service discovery approach is designed that furnished related web services based on user queries. The proposed strategy yields an accuracy of 90.4 % which is much better than the existing approaches.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130454599","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}

引用次数: 16

Evaluating Machine Learning Models for Disparate Computer Systems Performance Prediction 评估不同计算机系统性能预测的机器学习模型

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198512

Amit Mankodi, Amit Bhatt, B. Chaudhury, Rajat Kumar, Aditya Amrutiya

{"title":"Evaluating Machine Learning Models for Disparate Computer Systems Performance Prediction","authors":"Amit Mankodi, Amit Bhatt, B. Chaudhury, Rajat Kumar, Aditya Amrutiya","doi":"10.1109/CONECCT50063.2020.9198512","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198512","url":null,"abstract":"Performance prediction is an active area of research due to its applicability in the advancements of hardware-software co-development. Several empirical machine-learning models, such as linear models, non-linear models, probabilistic models, tree-based models and, neural networks, are used for performance prediction. Furthermore, the prediction model’s accuracy may vary depending on performance data gathered for different software types (compute-bound, memory-bound) and different hardware (simulation-based or physical systems). We have examined fourteen machine-learning models on simulation-based hardware and physical systems by executing several benchmark programs with different computation and data access patterns. Our results show that the tree-based machine-learning models outperform all other models with median absolute percentage error (MedAPE) of less than 5% followed by bagging and boosting models that help to improve weak learners. We have also observed that prediction accuracy is higher on simulation-based hardware due to its deterministic nature as compared to physical systems. Moreover, in physical systems, the prediction accuracy of memory-bound algorithms is higher as compared to compute-bound algorithms due to manufacturer variability in processors.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124596689","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}

引用次数: 3

Improved Glaucoma Diagnosis Using Deep Learning 利用深度学习改进青光眼诊断

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198524

Saumya Borwankar, R. Sen, Bhavin Kakani

引用次数: 5

Metamaterial Inspired Compact Penta-band Antenna For Wi-MAX, WLAN, Satellite band and X-band Applications 超材料启发紧凑型五波段天线，适用于Wi-MAX, WLAN，卫星波段和x波段应用

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198480

Y. V. Bhasakar Reddy, A. M. Prasad, K. Swamy

引用次数: 5

Development of Energy Meter Monitoring System (EMMS) for Data Acquisition and Tampering Detection using IoT 基于物联网的数据采集和篡改检测电能表监控系统(EMMS)的开发

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198495

M. A. P. Kamatagi, M. R. B. Umadi, M. V

{"title":"Development of Energy Meter Monitoring System (EMMS) for Data Acquisition and Tampering Detection using IoT","authors":"M. A. P. Kamatagi, M. R. B. Umadi, M. V","doi":"10.1109/CONECCT50063.2020.9198495","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198495","url":null,"abstract":"Electricity Crisis has become a serious issue, since the demand of power is increased over its production. One of the major challenges in electricity management is misuse of the power consumption due to electricity theft in public area. Energy Meter Monitoring System (EMMS) comprises of Raspberry Pi board and it mainly focuses on the implementation concept of Internet of Things (IoT) as the underlying framework to achieve real time monitoring of energy meter readings. The main theme is to have a system which can be installed with existing electronic meters, instead of developing a new smart meter. Raspberry pi connected to the meter continuously monitors the data sent by energy meter, read the data and print the actual values of parameters. These actual values of parameters are further communicated along with decimals and appropriate SI units. Go-daddy’s web server is developed and its database will store the data from the energy meter in front of its serial number. A multipurpose android application is designed to get the information regarding voltage ratings, current ratings, energy consumption and the meter tampering details which further can be useful to take actions against those customers. Upon providing the serial number of meter in the application, tampering status of energy meter is traced along with the basic parameter values.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132613194","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}

引用次数: 5

A Compact Circular Waveguide Polarizer with Higher Order Mode Excitation 具有高阶模激励的紧凑圆波导偏振器

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198499

Ashish Chittora, S. Yadav

引用次数: 21

Non-Invasive Computational Modeling of Heart from Vectorcardiography in Myocardial Infarction using Magnetocardiography 心肌梗死的心脏磁图无创计算建模

2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2020-07-01 DOI: 10.1109/CONECCT50063.2020.9198607

V. Bhat, A. H, Gireesan K

{"title":"Non-Invasive Computational Modeling of Heart from Vectorcardiography in Myocardial Infarction using Magnetocardiography","authors":"V. Bhat, A. H, Gireesan K","doi":"10.1109/CONECCT50063.2020.9198607","DOIUrl":"https://doi.org/10.1109/CONECCT50063.2020.9198607","url":null,"abstract":"Computational imaging of the cardio-magnetic sources is an emerging field in the biomedical society that promises to evaluate many cardiac related diseases without noninvasive procedures. The functional waves generated in terms of bio-magnetic field due to cardiac impulses can be investigated using Magnetocardiogram. The challenging task in the research is to image/localize the cardiac dysfunctions from MCG not only at the body surface but also to reconstruct the activities on the myocardial level. In order to solve this, one has to model a generic structure of the heart enclosed within a thorax with MCG sensors called as Forward problem.We proposed a novel approach in the construction of the spatial matrix derived from the vectorcardiography signals. The forward matrix was then used to estimate the position, orientation and the cardiac activities. The forward and inverse methods were applied to normal and myocardial infarcted cases for single and distributed source models. The localization accuracies of the proposed model based on VCG lied in the range of 0.01mm to 1 mm.The cardiac activities were estimated and compared using L2 norm and L1 norm regularization techniques. According to this study, the proposed spatial matrix used in the inverse problem gave good localization and L1 norm regularization provided sharper solutions than L2 norm.","PeriodicalId":261794,"journal":{"name":"2020 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130670232","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}

引用次数: 0