2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)最新文献_第2页

The optimal on-site generation allocation in a radial distribution system using GA and PSO 基于遗传算法和粒子群算法的径向配电系统现场发电优化分配

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708570

K. Rajesh, J. Rao

引用次数: 0

Smart Approaches to Measure Soil Fertility for Sustainable Agriculture 测量可持续农业土壤肥力的智能方法

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708578

R. S. Upendra, M. R. Ahmed, A. Omkar, Jhanvi Goyal, V. Chaitra, H. Muskan, Pragati Kamath, K. Thirumala Akash

{"title":"Smart Approaches to Measure Soil Fertility for Sustainable Agriculture","authors":"R. S. Upendra, M. R. Ahmed, A. Omkar, Jhanvi Goyal, V. Chaitra, H. Muskan, Pragati Kamath, K. Thirumala Akash","doi":"10.1109/ICSTCEE54422.2021.9708578","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708578","url":null,"abstract":"India is basically agriculture driven country and our GDP is principally directed by the yield of Rabi and Kharif crops. Most of the farmers of our country practices traditional way of agriculture. Since the amount of soil nutrients regulates the growth and quality of the crop, a systematic and quantitative analysis of soil nutrients is essential for good and adequate agricultural produce. Many small and large-scale farmers of the country India were not aware about the soil fertility nutrients and hence are unable to make use of their farming land efficiently for enhanced crop yield. The motive of the present work is to emphasize the significance of soil vitamins and the sensor based smart way of nutrient evaluation practices for measuring each essential nutrients i. e., Nitrogen, Phosphorus, and Potassium of Agri land. It was understood from the literature that, insufficient levels of essential elements (N, P, K) in farming lands can cause major issues connected with crop growth, productivity, and crop failure. To enlighten farmers and the readers with the smart farming practices, present study submitted a cumulative review on soil nutrient analysis methods with special emphasis on sensors based smart methods to measure the quantities of soil essential elements such as N, P, K. It has been concluded that potentiometric based electrochemical sensors are beneficial for soil testing and were found to be advantageous to farmers in keeping a constant check on their soil health, which intern enable the farmers to grow healthier crops and to maintain the surrounding soil biodiversity.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"110 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":"124683282","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

A Review of Blockchain Based Approach for Secured Communication in Internet of Vehicle (IoV) Scenario 基于区块链的车联网(IoV)场景安全通信方法综述

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708555

F. Azam, Arun Biradar, Neeraj Priyadarshi, S.Vijaya kumari, Shrikant S. Tangade

引用次数: 0

Logistic Regression versus XGBoost: Machine Learning for Counterfeit News Detection 逻辑回归与XGBoost:假新闻检测的机器学习

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708587

V. C. S. Rao, Pulyala Radhika, Niranjan Polala, Siripuri Kiran

{"title":"Logistic Regression versus XGBoost: Machine Learning for Counterfeit News Detection","authors":"V. C. S. Rao, Pulyala Radhika, Niranjan Polala, Siripuri Kiran","doi":"10.1109/ICSTCEE54422.2021.9708587","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708587","url":null,"abstract":"In this age of globalization, the unstoppable spreading of fake news via the internet is unstoppable. The spread of false news cannot be supported due to the negative consequences. Society is extremely concerning. In addition, itleads to more serious problems and possible threats, like confusion, misunderstandings, defamation and falsehoods that induce users to share inflammatory content. With the convenience and tremendous increase in information gathering on social networks, it is becoming difficult to differentiate between what is false and what is real. Information can be easily disseminated through sharing, which has contributed to the exponential growth of their forgeries. Machine learning played an important role, in classifying information, although there are some limitations. This article explores various machine learning techniques used to detect fake and fabricated messages. The limitations are discussed using deep learning implementation. In this project, the methodology used is model development and Logistic Regression classifier is considered to detect false news. Based on previous research, this classifier performed well in classification tasks. In this approach, TF-IDF feature is used for the construction of this fake news model to get higher accuracy. The goal of this project is to detect false news using NLP and Machine Learning based on the news content of the article. Following the development of the appropriate Machine Learning model to detect fake/true news, it is deployed into a web interface using Python Flask.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"9 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":"115104910","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

High Performance VLSI Architecture of Multiplexer and Demultiplexer Using various Adiabatic Logic 采用各种绝热逻辑的多路复用器和解路复用器的高性能VLSI架构

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708556

S. Karunakaran, P. Snehith

{"title":"High Performance VLSI Architecture of Multiplexer and Demultiplexer Using various Adiabatic Logic","authors":"S. Karunakaran, P. Snehith","doi":"10.1109/ICSTCEE54422.2021.9708556","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708556","url":null,"abstract":"Using adiabatic logics, we proposed the design and evaluation of a 1:16 Multiplexer and a 16:1 De-Multiplexer in this paper. We used traditional static CMOS logic to implement a 1:16 Multiplexer and a 16:1 De-multiplexer to compare the strength of static cmos logic and adiabatic logic. In many vlsi designs, power consumption is the most important factor. We used adiabatic logics to implement a 1:16 Multiplexer and 16:1 Demultiplexer in static CMOS logic to minimize power consumption. The adiabatic logics are 2N2P and 2N2N2P where in both the adiabatic logics use cross-coupled transistor for adiabatic operation. Adiabatic logic uses reverse logic and energy recovery technique that results in less power dissipation when compared to static CMOS logic. In static CMOS logic, we will give constant power source as Vdd. So, the total energy gets dissipated across the resistor, the energy stored by the capacitor will be very less because of this energy recovery is not happened as in case of static CMOS logic. In adiabatic logic we will give slowly varying ramp signal as vdd. So, the total energy is not dissipated across resistor and the capacitor starts charging. In the discharging phase the energy stored by the capacitor is sent back to the source because of this energy consumption is reduced. This is the energy recovery technique which happens in adiabatic logics.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 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":"121338791","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

A Discrete Fourier Transform Based Fault Identification Scheme for IEEE 9-bus System 基于离散傅立叶变换的IEEE 9总线系统故障识别方法

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708579

B. Chatterjee, Subhrajyoti Sarkar

引用次数: 0

ConvNet Based Detection and Segmentation of Brain Tumor from MR Images 基于卷积神经网络的脑肿瘤MR图像检测与分割

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708592

Valaparla Rohini, Kuchipudi Prasanth Kumar

引用次数: 1

Machine Learning based Cardiac Magnetic Resonance Imaging (CMRI) for Cardiac Disease Detection 基于机器学习的心脏磁共振成像(CMRI)用于心脏病检测

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708573

M. Ramesh, S. Mandapati, B. Prasad, B. Kumar

{"title":"Machine Learning based Cardiac Magnetic Resonance Imaging (CMRI) for Cardiac Disease Detection","authors":"M. Ramesh, S. Mandapati, B. Prasad, B. Kumar","doi":"10.1109/ICSTCEE54422.2021.9708573","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708573","url":null,"abstract":"The electrocardiogram (ECG) is a graphical representation of the heart’s electrical activity generated by contraction and relaxation of the heart muscle. An ECG is a vital tool for diagnosing heart conditions. The ECG flag is required for patient care. Early detection of heart disease allows specialists to differentiate between heart illnesses. A growing number of heart diseases necessitated the development of automatic abnormality detection techniques to relieve physicians. Cardiac magnetic resonance (CMR) images are becoming increasingly important in the diagnosis and monitoring of cardiovascular diseases in the nanomaterial of the kernels. As a result of the large amount and diversity of the data available, there are still many unanswered questions when it comes to the description and characterization of nanomaterial. Biomaterials characterization requires minimal information, which can be provided by AI and machine learning algorithms. These representations are also intended to provide an estimate of the CMR image quality in order to facilitate better interpretation and analysis of the CMR images. Also investigated, how quantitative analysis can be used to benefit from the use of these learned image representations during the process of image synthesis.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"2 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":"129343341","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

Cryogenic liquid level detection using fiber Bragg grating sensor 利用光纤光栅传感器进行低温液位检测

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708585

Sharath Umesh, L. S. Rajan, VV Lakshmi Pathi, Pramod Bandiwad, S. Elumalai, K. Sriram

{"title":"Cryogenic liquid level detection using fiber Bragg grating sensor","authors":"Sharath Umesh, L. S. Rajan, VV Lakshmi Pathi, Pramod Bandiwad, S. Elumalai, K. Sriram","doi":"10.1109/ICSTCEE54422.2021.9708585","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708585","url":null,"abstract":"Cryogenic liquid level detection plays a significant role during the filling of fuel (liquid hydrogen/liquid oxygen) to cryogenic stage in launch vehicles. Optical fiber sensors have been employed for cryogenic liquid level detection utilizing either intensity modulation by refractometry method or wavelength modulation by heat exchange efficiency method. The present study reports a novel wavelength modulation methodology employing multiplexed Fiber Bragg Grating (FBG) Sensors to assess the cryogenic liquid level in a storage tank. Two FBGs bonded over a resistance heater rod 20cm apart act as the sensing element, which will be immersed in the cryogenic fluid. The temperature of the sensing element is periodically increased and corresponding thermal responses of both the FBG sensors are acquired. Heat conductance capacity of cryogenic fluid is higher in liquid state than in gaseous state. The thermal responses of the FBG sensor obtained by assessing the heat transfer characteristics of the surrounding environment, will ascertain its existence in liquid or gaseous cryogenic fluid. By experimental investigation, it is observed that the thermal responses of the FBGs can actively discern between the liquid and gaseous states of cryogenic fluids. Further, with multiplexing capability, numerous FBGs can be fabricated in a single strand of fiber which can be discreet sensing points in order to assess the cryogenic liquid level.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"34 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":"128105307","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

A Convolutional Neural Network Based Approach for Computational Fluid Dynamics 基于卷积神经网络的计算流体力学方法

2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE) Pub Date : 2021-12-16 DOI: 10.1109/ICSTCEE54422.2021.9708548

Satyadhyan Chickerur, P. Ashish

{"title":"A Convolutional Neural Network Based Approach for Computational Fluid Dynamics","authors":"Satyadhyan Chickerur, P. Ashish","doi":"10.1109/ICSTCEE54422.2021.9708548","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708548","url":null,"abstract":"Computational fluid dynamics (CFD) is the visualisation of how a fluid moves and interacts with things as it passes by using applied mathematics, physics, and computational software. The project is designed to simulate fluid flow of a particle based on provided boundary conditions using High Performance Computing (HPC), with two-dimensional picture files as input to the software and fluid flow of a particle generated based on these image data. The Naiver Stokes Equation and the Lattice Boltzmann Equation are used to create these fluid flow particles.The governing equations based on the conservation law of fluid physical characteristics lead the primary structure of thermofluids investigations. Fluid flow is created depending on the item using the three governing equations from the conservation laws of physics. CFD simulation, on the other hand, which is a Iterative process is frequently computationally costly, memory-intensive, and time-consuming. A model based on convolutional neural networks, is proposed for predicting non-uniform flow in 2D to over come these disadvantages. The proposed approach thus aims to aid the behaviour of fluid particles on a certain system and to assist in the development of the system based on the fluid particles that travel through it. At the early stages of design, this technique can give quick feedback for real-time design revisions. In comparison to previous approximation methods in the aerodynamics domain, CNNs provide for efficient velocity field estimate and took less time then the previous approximation method. As CFD based CNN model is more effective to 2D design(2D aeroplane dataset) as it is in research stage lot more experiments have to be made for 3D designs. Designers and engineers may also use the CFD based CNN model directly in their 2D design space exploration.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"40 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":"127570689","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