2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)最新文献_第7页

Control of Standalone DFIG based Wind Turbine Generator using Machine Learning Algorithm 单机DFIG风力发电机的机器学习控制

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297603

R. Mahalakshmi, K. Reddy, M. Gautam

引用次数: 2

Design and Implementation of Multiple PWM Channels using Universal Asynchronous Receiver Transmitter 多PWM通道通用异步收发器的设计与实现

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297566

Shikhar

{"title":"Design and Implementation of Multiple PWM Channels using Universal Asynchronous Receiver Transmitter","authors":"Shikhar","doi":"10.1109/ICECA49313.2020.9297566","DOIUrl":"https://doi.org/10.1109/ICECA49313.2020.9297566","url":null,"abstract":"Universal Asynchronous Receiver Transmitter (UART) is a communication protocol used for sending and receiving the serial data. It offers short distance communication and it is reliable as well. This paper presents the application of UART module for creating Multiple Pulse Width Modulation (PWM) channels having different duty cycles using serial terminal on Field Programmable Gate Arrays (FPGA). The user can control the duty cycle of the PWM signals through serial terminal. UART module designed for this application features technique for baud rate detection. The design has been synthesized using Verilog Hardware Description Language (HDL) on Lattice Mach XO2 FPGA over a Tiny FPGA A2 module using Lattice Diamond Design software. A Printed Circuit Board (PCB) has been designed to observe the effects of PWM signals with different duty cycles over multiple Light Emitting Diodes (LEDs). The design is verified through simulations and logic analyzer tool. Effects of PWM signals is also observed through the intensity of Multiple LEDs. Maximum frequency that can be obtained on Lattice Mach XO2 FPGA is 133 MHz. The design uses 12.08 MHz frequency for the system clock.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123546416","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

Improved Trust Model based on Centrality Measures and Recommendation in Social Network 基于社交网络中心性度量和推荐的改进信任模型

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297562

Aseel Hussein Zahi, Dr. Saad Talib Hasson

{"title":"Improved Trust Model based on Centrality Measures and Recommendation in Social Network","authors":"Aseel Hussein Zahi, Dr. Saad Talib Hasson","doi":"10.1109/ICECA49313.2020.9297562","DOIUrl":"https://doi.org/10.1109/ICECA49313.2020.9297562","url":null,"abstract":"In this article, a model is developed to improve trust value in the relations that represents social networks by utilizing centrality measures interred with all participants in network-based and recommendations, both on connection or trust. Various central metrics were discussed and implemented to intend to trust. Algorithms are provided to facilitate their calculations. The referral neighbor that has a guaranteed trust boundary is chosen. Trust Value based on Interaction and Recommendations using Centrality Metric (TVIRCM) method is proposed and implemented in this study to improve trust value in the social network when the link between any two nodes represent the unique indication about trust whereas, there are no other standards for maintaining trust. Trust based on interaction refers to trust calculations based on real links observations and exploits the centrality metric. Trust based on recommendation refers to trust calculation based on trust participants of a remote neighbor about other participants.The developed approach is utilized in a trust observation phase as a trust-based interaction (i.e. assigned high and low centrality metrics), then the next phase is based on the proposed recommendation (i.e. the remote neighbor may have certain trust value) and the last phase is the trust calculation phase which based on combining direct and indirect trust.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124939796","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

An Improvised Analysis in the Parameter of a Conventional Microstrip Patch Antenna for 5G Communication 5G通信中传统微带贴片天线参数的临时分析

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297543

P. Patel, D. K. Meda

引用次数: 0

Pixel based method for Text to Image Encryption 基于像素的文本到图像加密方法

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297478

K. Malathi, R. Kavitha, M. Liza

引用次数: 3

Artificial Bee Colony assisted Spectrum Sharing Scheme for NOMA based Cognitive Radio Networks 基于NOMA认知无线网络的人工蜂群辅助频谱共享方案

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297496

K. Sultan

{"title":"Artificial Bee Colony assisted Spectrum Sharing Scheme for NOMA based Cognitive Radio Networks","authors":"K. Sultan","doi":"10.1109/ICECA49313.2020.9297496","DOIUrl":"https://doi.org/10.1109/ICECA49313.2020.9297496","url":null,"abstract":"In this paper, a cooperative spectrum sharing scheme is proposed for NOMA based cognitive radio networks comprising of primary and secondary networks. The primary network consists of a primary transmitter PT communicating with a primary receiver PU, whereas the secondary network consists of a NOMA based secondary transmitter ST communicating with L secondary users SUs. The primary terminals are separated far apart therefore ST provides assistance as a relay in order to enable their end-to-end communication. Each terminal is equipped with a single antenna therefore end-to-end communication is accomplished in two time-slots. In first timeslot, PT transmits its signal to ST and at the same time one best SU retransmits the primary signal of the last frame to PU. In second time-slot, ST transmits the superimposed signals of primary and secondary networks. In this scenario, sum rate of SUs is maximized while ensuring to guarantee the QoS of PU. Artificial Bee Colony (ABC) global optimization algorithm is employed to solve this transmit power allocation problem which quickly converged to the best solution.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"127 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128024353","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

Detection of Arrhythmia using ECG waves with Deep Convolutional Neural Networks 基于深度卷积神经网络的心电波检测心律失常

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297467

A. Gowtham, L. Anirudh, B. Sreeja, BA Aakash, S. Adittya

{"title":"Detection of Arrhythmia using ECG waves with Deep Convolutional Neural Networks","authors":"A. Gowtham, L. Anirudh, B. Sreeja, BA Aakash, S. Adittya","doi":"10.1109/ICECA49313.2020.9297467","DOIUrl":"https://doi.org/10.1109/ICECA49313.2020.9297467","url":null,"abstract":"If there is an availability of technological medical electronic devices to classify heart disease, it would absolutely change the future in terms of making it more economical and qualitative for all the people suffering from heart-related ailments. With the increasing medical expenses and non-affordability of the poor families, it becomes logical to design a system that can detect heart disease in particular Arrhythmia, without higher expense. Recently, the Cardiovascular systems are evaluated more reliably by using Electrocardiogram (ECG) waves. This project in particular is designed to check for any irregularities in heart beats, which is represented in the variations of an ECG wave, and then compared it with normal beats to detect Arrhythmia. The electronics behind this project is Raspberry Pi and ADS1115, an ADC, which converts the real-time, analog ECG wave signal into a digital wave with the help of heart rate sensor-AD8232, and a three-lead system. A normalized wave is fed into the deep convolutional neural network to predict the output into one of the 5 different categories. Furthermore, the ADASYN – Adaptive Synthetic Sampling - algorithm is used to effectively classify the disease in accordance with the MIT-BIH dataset.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129016170","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

Design of Low Power & High Speed Comparator of SAR ADC using 180nm Technology 基于180nm技术的SAR ADC低功耗高速比较器设计

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297473

Harshita kushwah, R. Gamad, R. Gurjar

引用次数: 0

A Comparative Study of Activation Functions and Training Algorithm of NAR Neural Network for Crop Prediction 作物预测中NAR神经网络激活函数与训练算法的比较研究

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297469

V. Kaleeswaran, S. Dhamodharavadhani, R. Rathipriya

引用次数: 5

Machine Learning Techniques for Depression Analysis on Social Media- Case Study on Bengali Community 社交媒体上抑郁症分析的机器学习技术——以孟加拉社区为例

2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA) Pub Date : 2020-11-05 DOI: 10.1109/ICECA49313.2020.9297436

Debasish Bhattacharjee Victor, Jamil Kawsher, Md Shad Labib, Subhenur Latif

{"title":"Machine Learning Techniques for Depression Analysis on Social Media- Case Study on Bengali Community","authors":"Debasish Bhattacharjee Victor, Jamil Kawsher, Md Shad Labib, Subhenur Latif","doi":"10.1109/ICECA49313.2020.9297436","DOIUrl":"https://doi.org/10.1109/ICECA49313.2020.9297436","url":null,"abstract":"Depression is a prevalent illness in todays society. It changes and influences our entire method of thought and our emotional, cognitive, and everyday behavioral behaviors. It affected over 264 million people, and the proportion increases every day. Mainly when it lasts for a prolonged time, it becomes a severe issue or health topic. It leads the trustworthy person to also malfunction, and that person commits suicide in his final position. There are several causes for depression, though social networking like Facebook, Twitter, and other networking plays a critical role in getting us more depressed. Most people in Asia use Facebook, Twitter, and various chat applications, and there they express their emotions. That is why our research initiative picks social media. Some work has been done on depression but depression detection on the Bengali community is done very rarely. So it has become a strong demand for today. The social media has intialted a study based on depression, tweets, and numerous chat app responses, and gathered Bengali data and projected depression posts and commentaries. Diverse approaches of machine learning have been used to evaluate these data and forecast depression and for algorithm purpose Support vector machine, Random Forest, Decision Tree, K-Nearest Neighbors, Naive Bayes (Multinomial Naive Bayes), Logistic Regression has been used. The desired results can be obtained by adding those algorithms. Moreover, different algorithms send us different results as trends were common, but ultimately the precision was the same for all algorithms applied to our dataset.","PeriodicalId":297285,"journal":{"name":"2020 4th International Conference on Electronics, Communication and Aerospace Technology (ICECA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128863839","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: 8