2021 2nd Global Conference for Advancement in Technology (GCAT)最新文献_第3页

IoT Based Smart Traffic System Using MQTT Protocol: Node-Red Framework 使用MQTT协议的基于物联网的智能交通系统:节点-红框架

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587636

S. Bharath, C. Khusi

引用次数: 1

Hand-written Hindi Character Recognition - A Comprehensive Review 手写体印地语字符识别-综合评论

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587554

Awadh Kishor Singh, Bintu Kadhiwala, Rakesh Patel

引用次数: 1

A Deep Learning Based Assisted Tool for Atrial Fibrillation Detection Using Electrocardiogram 基于深度学习的心电图房颤检测辅助工具

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587503

S. Shrikanth Rao, M. Kolekar, R. J. Martis

{"title":"A Deep Learning Based Assisted Tool for Atrial Fibrillation Detection Using Electrocardiogram","authors":"S. Shrikanth Rao, M. Kolekar, R. J. Martis","doi":"10.1109/GCAT52182.2021.9587503","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587503","url":null,"abstract":"Atrial fibrillation (AF) is a disorder related to the heart. Irregularity of RR intervals and lack of P wave are the two main indicators of AF. Detection of AF using Electrocardiogram (ECG) remains one of the real challenges in the field of medical science. In this paper, we propose Discrete Wavelet Transform based method coupled with Deep Learning methods such as 2 layer Long Short Term Memory (LSTM) along with Gradient Recurrent Unit (GRU), 2 layer Bidirectional Long Short Term Memory (BiLSTM) along with Gradient Recurrent Unit (GRU) are used separately to classify the ECG signal into 3 classes namely: Normal, AF and other rhythms. Physionet challenge 2017 dataset is used for the study purpose. The results of LSTM and BiLSTM are compared with Support Vector Machine (SVM). The result indicated that LSTM provided improved performance compared to BiLSTM and SVM methods. The class specific accuracy of normal, AF and other rhythm are 96.92%, 97.36% and 96.39% respectively and Area Under the Curve (AUC) is 0.982. The overall accuracy of LSTM network is obtained as 96.94%. The developed technology has immense applications in medical devices.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132274276","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

A Framework for Detecting Cervical Cancer Based on UD-MHDC Segmentation and MBD-RCNN Classification Techniques 基于UD-MHDC分割和MBD-RCNN分类技术的宫颈癌检测框架

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587533

Meghana A Rajeev

引用次数: 0

Generative Adversarial Networks and their Miscellaneous Applications: A Review 生成对抗网络及其其他应用综述

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587496

Mayank Singhal, R. Agarwal

引用次数: 0

MEMS Piezoresistive Cantilever Fabrication And Characterization MEMS压阻悬臂梁的制造与表征

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587807

Miranji Katta, R. Sandanalakshmi

引用次数: 0

Machine Interpretation of Medical Images Using Deep Learning 使用深度学习的医学图像机器解释

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587518

Vidhi Chhatbar, Mihir Gondhalekar, Shruti Pimple, R. Pawar

引用次数: 0

Flyswatter Shaped Antenna for 8 Element Beam Forming Network utilizing Butler Matrix 基于巴特勒矩阵的八元波束形成网络的苍蝇拍形天线

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587529

Dilshan Singh Chadha, Kartikey Chaturvedi, M. D. Upadhayay

引用次数: 0

Early detection of ASD Traits in Children using CNN CNN在儿童ASD特征早期检测中的应用

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587648

N. Kaur, Vijay KumarSinha, S. Kang

{"title":"Early detection of ASD Traits in Children using CNN","authors":"N. Kaur, Vijay KumarSinha, S. Kang","doi":"10.1109/GCAT52182.2021.9587648","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587648","url":null,"abstract":"Autism is neurological disorder in which person is affected with communication and interaction abilities. Lacks of social interaction, repetitive behavior, and stable interest are indication of the autistic child. It essential to identify the autism at very is early stage. CNN plays vital role in health care which requires a process that reduces cost and time. The key objective of proposed paper is to implement convolution neural network algorithms and classify autistic and non-autistic child..In this study, CNN is applied for classification of autistic and non-autistic child. The images of children of age 4 to 11 years were used. About 400 images extracted from pre-defined datasets and were used to train the CNN algorithm using the Google colab framework via Python and Open CV libraries. Using cross validation techniques, The CNN was evaluated. In this sense, our proposed model has achieved a high accuracy rate and robustness for prediction of autistic and non-autistic child. Additionally, the proposed algorithm attains a quick response time. Therefore, we could significantly diminish the time of diagnosis by applying the proposed method and facilitate the diagnosis of ASD in lower cost.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114941062","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 and Implementation of Articulated Mimicking Robotic Finger with Abduction and Adduction Movements in the Index MCP Joint and Thumb CMC Joint 食指MCP关节和拇指CMC关节外展内收关节模拟机械手指的设计与实现

2021 2nd Global Conference for Advancement in Technology (GCAT) Pub Date : 2021-10-01 DOI: 10.1109/GCAT52182.2021.9587750

Andrian C. Monroy, Kurt Austin Padilla, Edwin R. Rillera, Jepthah D. Rodriguez, Kenneth Oliver Y. Tindugan, R. Tolentino

{"title":"Design and Implementation of Articulated Mimicking Robotic Finger with Abduction and Adduction Movements in the Index MCP Joint and Thumb CMC Joint","authors":"Andrian C. Monroy, Kurt Austin Padilla, Edwin R. Rillera, Jepthah D. Rodriguez, Kenneth Oliver Y. Tindugan, R. Tolentino","doi":"10.1109/GCAT52182.2021.9587750","DOIUrl":"https://doi.org/10.1109/GCAT52182.2021.9587750","url":null,"abstract":"In this study, the proponents proposed a mechanism that provides abduction and adduction movements at the MCP joint of index finger and CMC joint of the thumb as well as full actuation in the movements of remaining joints whose human equivalents are capable of fully-independent movement. The system consists of two main digits: the thumb and the index finger. As a rundown, the digits are actuated by several HS35HD Micro Servo Motors, MG996R High-Torque Motor, and PQ-12R Micro Linear Servo. An aspect that can be noticed in the mechanism is the movement in the index PIP joint is actuated by a linear servo whose linear movement translated into rotational movement, with the mechanism allowing the distal phalange of the finger to move dependently of the middle phalange.A series of flex sensors attached on a glove was used to gather finger joint movement data made by the user. Mimicking happens as motors actuate according to the gathered data with the help of Arduino Mega 2560. To compare the angular positions actuated by the motors to that of the movements by the user flex sensors and potentiometer were utilized. The system’s mimicking capability is then evaluated using z-test.","PeriodicalId":436231,"journal":{"name":"2021 2nd Global Conference for Advancement in Technology (GCAT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116011298","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