International Journal of Intelligent Systems and Applications in Engineering最新文献_第6页

Classification of COVID-19 Cases using Deep Neural Network based on Chest Image Data through WSN 基于WSN胸部图像数据的深度神经网络新冠肺炎病例分类

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.264

V. V, S. Nisha A., N. R., Amirthalakshmi T. M., B. Velan

{"title":"Classification of COVID-19 Cases using Deep Neural Network based on Chest Image Data through WSN","authors":"V. V, S. Nisha A., N. R., Amirthalakshmi T. M., B. Velan","doi":"10.18201/ijisae.2022.264","DOIUrl":"https://doi.org/10.18201/ijisae.2022.264","url":null,"abstract":"Due to the rapid spread of corona virus disease (COVID-19), it has been considered as a pandemic throughout the world. The misclassification of COVID-19 cases may even lead the death of the patients, and hence the diagnosis at early stage is important to stop further spread of the infection and to safeguard the life of the patients. This paper proposes the Aquila tuned Deep neural network (Aquila-DNN) classifier for the classification of COVID-19 patients using the chest image data assessed through Wireless sensor Network (WSN). The extraction of important features from the chest image data is important in the diagnosis as it encloses the important data of the patients. The optimal tuning of the DNN parameters using the Aquila Optimizer (AO) assists in improving the classification accuracy of proposed model. In addition, the convergence is also boosted using the tuning process of the AO algorithm. The effectiveness of the proposed Aquila-DNN model is validated with the analysis of the model based on the performance indices, namely accuracy, ROC curve, and F1 measure. The testing accuracy and the training accuracy of Aquila-DNN model are attained to be 99.7%, and 95.4545%, respectively. © 2022, Ismail Saritas. All rights reserved.","PeriodicalId":14067,"journal":{"name":"International Journal of Intelligent Systems and Applications in Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44809874","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 Novel Screening Tool System for Depressive Disorders using Social Media and Artificial Neural Network 一种基于社交媒体和人工神经网络的抑郁症筛查工具系统

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.274

A. M. Baes, A. J. Adoptante, John Carlo A. Catilo, Patrick Kendrex L. Lucero, Janice F. Peralta, Anton Louise P. de Ocampo

引用次数: 3

Detecting Face-Touch Hand Moves Using Smartwatch Inertial Sensors and Convolutional Neural Networks 使用智能手表惯性传感器和卷积神经网络检测面部触摸手势

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.275

E. Sehirli, Abdullah Alesmaeil

{"title":"Detecting Face-Touch Hand Moves Using Smartwatch Inertial Sensors and Convolutional Neural Networks","authors":"E. Sehirli, Abdullah Alesmaeil","doi":"10.18201/ijisae.2022.275","DOIUrl":"https://doi.org/10.18201/ijisae.2022.275","url":null,"abstract":"As per World Health Organization (WHO), avoiding touching the face when people are in public or crowded places is an effective way to prevent respiratory viral infections. This recommendation has become more crucial with the current health crisis and the worldwide spread of COVID-19 pandemic. However, most face touches are done unconsciously, that is why it is difficult for people to monitor their hand moves and try to avoid touching the face all the time. Hand-worn wearable devices like smartwatches are equipped with multiple sensors that can be utilized to track hand moves automatically. This work proposes a smartwatch application that uses small, efficient, and end-to-end Convolutional Neural Networks (CNN) models to classify hand motion and identify Face-Touch moves. To train the models, a large dataset is collected for both left and right hands with over 28k training samples that represents multiple hand motion types, body positions, and hand orientations. The app provides real-time feedback and alerts the user with vibration and sound whenever attempting to touch the face. Achieved results show state of the art face-touch accuracy with average recall, precision, and F1-Score of 96.75%, 95.1%, 95.85% respectively, with low False Positives Rate (FPR) as 0.04%. By using efficient configurations and small models, the app achieves high efficiency and can run for long hours without significant impact on battery which makes it applicable on most off-the-shelf smartwatches. © 2022, Ismail Saritas. All rights reserved.","PeriodicalId":14067,"journal":{"name":"International Journal of Intelligent Systems and Applications in Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41463441","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: 4

A Novel Approach for ABO Blood Group Prediction using Fingerprint through Optimized Convolutional Neural Network 基于优化卷积神经网络的指纹ABO血型预测新方法

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.268

Vijaykumar Patil, D. Ingle

引用次数: 4

Land use Land cover change Assessment at Cement Industrial area using Landsat data-hybrid classification in part of YSR Kadapa District, Andhra Pradesh, India 印度安得拉邦YSR Kadapa区部分地区土地利用土地覆盖变化评估

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.270

C. Sudhakar, G. Reddy

引用次数: 9

Automatic Pancreas Segmentation using A Novel Modified Semantic Deep Learning Bottom-Up Approach 一种新的改进语义深度学习自下而上的胰腺自动分割方法

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.272

Pradip M. Paithane, Dr. S. N. Kakarwal

引用次数: 7

Solving Arithmetic Word Problems Using Natural Language Processing and Rule-Based Classification 利用自然语言处理和基于规则的分类解决算术单词问题

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.271

Sourav Mandal, Swagata Acharya, Rohini Basak

引用次数: 2

A Study on the Development of a Core Patent Classification Model Using Improved Patent Performance Indicators 基于改进专利绩效指标的核心专利分类模型构建研究

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.261

Youngho Kim, Sangsung Park, Junseok Lee, J. Kang

引用次数: 0

SettingsAn Intelligent Assignment Problem Using Novel Heuristic: The Dhouib-Matrix-AP1 (DM-AP1) 设置一个使用新启发式的智能分配问题：Dhouib-Matrix-AP1（DM-AP1）

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.277

S. Dhouib

引用次数: 7

Comparison of Machine Learning Algorithms for Recognizing Drowsiness in Drivers using Electroencephalogram (EEG) Signals 利用脑电图(EEG)信号识别驾驶员睡意的机器学习算法比较

International Journal of Intelligent Systems and Applications in Engineering Pub Date : 2022-03-31 DOI: 10.18201/ijisae.2022.266

Rüya Akinci, E. Akdogan, Mehmet Emin Aktan

引用次数: 4