2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT)最新文献_第5页

Thermal load calculation of building envelope set up with the help of a drone setup 利用无人机对建筑围护结构进行热负荷计算

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837359

Mohammad Zeeshan, Md Rakeeb Alam, Osama Khan, M. Parvez, A. Azad

引用次数: 4

An enhanced hybrid approach for building of Question Answering Prototype 一种改进的混合式问答原型构建方法

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837348

Vikas Bali, A. Verma

引用次数: 0

Data Structures for Delay Reduction in Vehicular Ad hoc Networks 车辆自组织网络中时延降低的数据结构

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837383

Raghavendra Pal, R. Thenua

引用次数: 0

Modeling and Simulation of Grid Connected PV System 并网光伏系统建模与仿真

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837340

V. Katiyar, M. Ilyas, A. Azad

引用次数: 0

6G Communication: Next Generation Technology for IoT Applications 6G通信:物联网应用的下一代技术

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837375

Prashant Upadhyaya, S. Dutt, Ruchi, Sheetal Upadhyaya

引用次数: 3

Multi-broadcasting in Trees of a Given Diameter 在给定直径的树中进行多广播

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837363

Suruchi Gautam

引用次数: 0

To Analyze the Comprehensive Review MPPT Techniques of Wind Driven PMSG 风力驱动PMSG的MPPT技术综述分析

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837354

N. Agarwal, A. Rani, A. Saxena

引用次数: 0

Comparison and analysis of deep learning for Dehazing 深度学习用于除雾的比较与分析

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837357

Rajat Tiwari

引用次数: 0

Design of a High Speed and Low Power Charge Shared Based Dynamic Comparator for ADC Application 一种用于ADC的高速低功耗共享动态比较器的设计

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-12-16 DOI: 10.1109/icacfct53978.2021.9837362

N. Rai, Anurag Yadav, Subodh Wairya

{"title":"Design of a High Speed and Low Power Charge Shared Based Dynamic Comparator for ADC Application","authors":"N. Rai, Anurag Yadav, Subodh Wairya","doi":"10.1109/icacfct53978.2021.9837362","DOIUrl":"https://doi.org/10.1109/icacfct53978.2021.9837362","url":null,"abstract":"An ultimate requirement of the less power, high speed and energy efficient analog to digital converters(ADCs) have given immense popularity to dual stage positive feedback based clocked comparators. A high speed, low power dynamic comparator is addressed in this paper. The proposed architecture is based on charge shared logic in the regenerative latch stage along with modification in the pre-amplifier stage. The power consumption has been tremendously reduced by preventing the input nodes of pre-amplifier stage from completely decreasing to ground. The delay of the circuit is also reduced compared to conventional circuits of dynamic comparator .For verification of the outcome’s, all the architectures are simulated in 45-nm technology on Cadence Virtuoso at power supply voltage of 0.8V. The new architecture of dynamic comparator consumes a total power of 1.29 μW and delay of 112.44ps at maximum operating frequency of 1GHz with 0.8V supply voltage, common mode input voltage (Vcm) of 0.7V and difference in input voltage of 5mV. The Monte Carlo analysis for various mismatch effect occurring in the circuit is also shown along with process corner analysis.","PeriodicalId":312952,"journal":{"name":"2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122565738","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: 1

COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation 基于卷积神经网络和数据增强的咳嗽声学诊断COVID-19

2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT) Pub Date : 2021-10-12 DOI: 10.1109/icacfct53978.2021.9837350

Saranga Kingkor Mahanta, Darsh Kaushik, Shubham Jain, Hoang Van Truong, K. Guha

{"title":"COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation","authors":"Saranga Kingkor Mahanta, Darsh Kaushik, Shubham Jain, Hoang Van Truong, K. Guha","doi":"10.1109/icacfct53978.2021.9837350","DOIUrl":"https://doi.org/10.1109/icacfct53978.2021.9837350","url":null,"abstract":"With the periodic rise and fall of COVID-19 and countries being inflicted by its waves, an efficient, economic, and effortless diagnosis procedure for the virus has been the utmost need of the hour. Amongst the infected subjects, the asymptomatic ones need not be entirely free of symptoms caused by the virus. They might not show any observable symptoms like the symptomatic subjects, but they may differ from uninfected ones in the way they cough. These differences in the coughing sounds are minute and indiscernible to the human ear, however, these can be captured using machine learning models. In this paper, we present a deep learning approach to analyze the acoustic dataset provided in Track 1 of the DiCOVA 2021 Challenge containing cough sound recordings belonging to both COVID-19 positive and negative examples. To perform the classification we propose a ConvNet model. It achieved an AUC score percentage of 72.23 on a blind test set provided in the challenge for an unbiased evaluation of the models. Moreover, the ConvNet model incorporated with Data Augmentation further increased the AUC score percentage from 72.23 to 87.07. It also outperformed the DiCOVA 2021 Challenge’s baseline model by 23% thus, claiming the top position on the DiCOVA 2021 Challenge leaderboard. This paper proposes the use of Mel Frequency Cepstral Coefficients as the input features to the proposed model.","PeriodicalId":312952,"journal":{"name":"2021 First International Conference on Advances in Computing and Future Communication Technologies (ICACFCT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125453409","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: 7