Pub Date : 2023-08-01DOI: 10.3991/ijoe.v19i10.39489
M. Ed-Dhahraouy, Hicham Riri, M. Ezzahmouly, A. Elmoutaouakkil, Farid Bourzgui, H. El Byad
The aim of this study is to examine the influence of threshold-based segmentation on the mean error of automatic landmark detection in 3D CBCT images. A GUI was developed for radiologists, allowing manual landmark identification and visualization of CBCT images. After a threshold-based segmentation, a semi-automatic algorithm for landmark detection was designed using the anatomic definition of each landmark. A step of 50 Hounsfield units was used for threshold variation to assess the detection error. 5 CBCT images were used to validate the proposed approach. The measurement of error detection for one patient was influenced by the threshold variation. For this patient, the error changed from 1.49 mm to 10.32 mm at a low threshold value, while for another patient, the error changed from 1.96 mm to 12.28 mm at high a threshold value. In a CBCT scanner, the choice of threshold value for segmentation can be an important factor in causing error in measurements.
{"title":"Threshold-Based Segmentation for Landmark Detection Using CBCT Images","authors":"M. Ed-Dhahraouy, Hicham Riri, M. Ezzahmouly, A. Elmoutaouakkil, Farid Bourzgui, H. El Byad","doi":"10.3991/ijoe.v19i10.39489","DOIUrl":"https://doi.org/10.3991/ijoe.v19i10.39489","url":null,"abstract":"The aim of this study is to examine the influence of threshold-based segmentation on the mean error of automatic landmark detection in 3D CBCT images. A GUI was developed for radiologists, allowing manual landmark identification and visualization of CBCT images. After a threshold-based segmentation, a semi-automatic algorithm for landmark detection was designed using the anatomic definition of each landmark. A step of 50 Hounsfield units was used for threshold variation to assess the detection error. 5 CBCT images were used to validate the proposed approach. The measurement of error detection for one patient was influenced by the threshold variation. For this patient, the error changed from 1.49 mm to 10.32 mm at a low threshold value, while for another patient, the error changed from 1.96 mm to 12.28 mm at high a threshold value. In a CBCT scanner, the choice of threshold value for segmentation can be an important factor in causing error in measurements.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46665919","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}
Pub Date : 2023-08-01DOI: 10.3991/ijoe.v19i10.40381
Hicham Gibet Tani, Lamiae Eloutouate, F. Elouaai, M. Bouhorma, Mohamed Walid Hajoub
Image captioning is a promising technique for remote monitoring of patient behavior, enabling healthcare providers to identify changes in patient routines and conditions. In this study, we explore the use of transformer neural networks for image caption generation from surveillance camera footage, captured at regular intervals of one minute. Our goal is to develop and evaluate a transformer neural network model, trained and tested on the COCO (common objects in context) dataset, for generating captions that describe patient behavior. Furthermore, we will compare our proposed approach with a traditional convolutional neural network (CNN) method to highlight the prominence of our proposed approach. Our findings demonstrate the potential of transformer neural networks in generating natural language descriptions of patient behavior, which can provide valuable insights for healthcare providers. The use of such technology can allow for more efficient monitoring of patients, enabling timely interventions when necessary. Moreover, our study highlights the potential of transformer neural networks in identifying patterns and trends in patient behavior over time, which can aid in developing personalized healthcare plans.
{"title":"Transforming Healthcare: Leveraging Vision-Based Neural Networks for Smart Home Patient Monitoring","authors":"Hicham Gibet Tani, Lamiae Eloutouate, F. Elouaai, M. Bouhorma, Mohamed Walid Hajoub","doi":"10.3991/ijoe.v19i10.40381","DOIUrl":"https://doi.org/10.3991/ijoe.v19i10.40381","url":null,"abstract":"Image captioning is a promising technique for remote monitoring of patient behavior, enabling healthcare providers to identify changes in patient routines and conditions. In this study, we explore the use of transformer neural networks for image caption generation from surveillance camera footage, captured at regular intervals of one minute. Our goal is to develop and evaluate a transformer neural network model, trained and tested on the COCO (common objects in context) dataset, for generating captions that describe patient behavior. Furthermore, we will compare our proposed approach with a traditional convolutional neural network (CNN) method to highlight the prominence of our proposed approach. Our findings demonstrate the potential of transformer neural networks in generating natural language descriptions of patient behavior, which can provide valuable insights for healthcare providers. The use of such technology can allow for more efficient monitoring of patients, enabling timely interventions when necessary. Moreover, our study highlights the potential of transformer neural networks in identifying patterns and trends in patient behavior over time, which can aid in developing personalized healthcare plans.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":"212 4","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41258905","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}
The field of reconfigurable computing is gaining a lot of following, and several use cases have been developed for it. At the centre of reconfigurable computing is the field programmable gate array (FPGA) due to its computational speed and versatility. The goal of the work reported here was to show that a single FPGA board paired with a computer monitor can be used as the sole laboratory equipment in a cash-strapped educational institution or by an individual. A Terasic DE1-SoC board was programmed as an oscilloscope, and digital multimeter. In keeping with the low-cost theme of this work, no external signal conditioning circuit was used and the on-board LTC2308 ADC was used for signal acquisition. At frequencies below 15 kHz, the voltage measurements of the developed FPGA lab instrument had a mean error of 58 mV. The voltage measurement errors, however, increased with an increase in frequency and the errors were significant when the signal frequencies exceeded 100 kHz. In terms of the use of the FPGA to replace multiple lab instruments, 13% of the DSPs on the FPGA were used for the implementation and 80% of the Adaptive logic modules. We therefore demonstrate that with $300 dollars, multiple pieces of laboratory equipment can be replaced by a single FPGA board and a monitor.
{"title":"A Case for Low-Cost Personal Electronic Laboratory Equipment using FPGAs","authors":"Timothy Olanrewaju Adegbite, Olawale Babatunde Akinwale","doi":"10.3991/ijoe.v19i10.39487","DOIUrl":"https://doi.org/10.3991/ijoe.v19i10.39487","url":null,"abstract":"The field of reconfigurable computing is gaining a lot of following, and several use cases have been developed for it. At the centre of reconfigurable computing is the field programmable gate array (FPGA) due to its computational speed and versatility. The goal of the work reported here was to show that a single FPGA board paired with a computer monitor can be used as the sole laboratory equipment in a cash-strapped educational institution or by an individual. A Terasic DE1-SoC board was programmed as an oscilloscope, and digital multimeter. In keeping with the low-cost theme of this work, no external signal conditioning circuit was used and the on-board LTC2308 ADC was used for signal acquisition. At frequencies below 15 kHz, the voltage measurements of the developed FPGA lab instrument had a mean error of 58 mV. The voltage measurement errors, however, increased with an increase in frequency and the errors were significant when the signal frequencies exceeded 100 kHz. In terms of the use of the FPGA to replace multiple lab instruments, 13% of the DSPs on the FPGA were used for the implementation and 80% of the Adaptive logic modules. We therefore demonstrate that with $300 dollars, multiple pieces of laboratory equipment can be replaced by a single FPGA board and a monitor.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48964830","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.39927
Parsipogu Glory Veronica, Ravi Kumar Mokkapati, Lakshmi Prasanna Jagupilla, Chella Santhosh
Hand tracking and identification through visual means pose a challenging problem. To simplify the identification of hand gestures, some systems have incorporated position markers or colored bands, which are not ideal for controlling robots due to their inconvenience. The motion recognition problem can be solved by combining object identification, recognition, and tracking using image processing techniques. A wide variety of target detection and recognition image processing methods are available. This paper proposes novel CNN-based methods to create a user-free hand gesture detection system. The use of synthetic techniques is recommended to improve recognition accuracy. The proposed method offers several advantages over existing methods, including higher accuracy and real-time hand gesture recognition suitable for sign language recognition and human-computer interaction. The CNN automatically extracts high-level characteristics from the source picture, and the SVM is used to classify these features. This study employed a CNN to automatically extract traits from raw EMG images, which is different from conventional feature extractors. The SVM classifier then determines which hand gestures are being made. Our tests demonstrate that the proposed strategy achieves superior accuracy compared to using only CNN.
{"title":"Static Hand Gesture Recognition Using Novel Convolutional Neural Network and Support Vector Machine","authors":"Parsipogu Glory Veronica, Ravi Kumar Mokkapati, Lakshmi Prasanna Jagupilla, Chella Santhosh","doi":"10.3991/ijoe.v19i09.39927","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.39927","url":null,"abstract":"Hand tracking and identification through visual means pose a challenging problem. To simplify the identification of hand gestures, some systems have incorporated position markers or colored bands, which are not ideal for controlling robots due to their inconvenience. The motion recognition problem can be solved by combining object identification, recognition, and tracking using image processing techniques. A wide variety of target detection and recognition image processing methods are available. This paper proposes novel CNN-based methods to create a user-free hand gesture detection system. The use of synthetic techniques is recommended to improve recognition accuracy. The proposed method offers several advantages over existing methods, including higher accuracy and real-time hand gesture recognition suitable for sign language recognition and human-computer interaction. The CNN automatically extracts high-level characteristics from the source picture, and the SVM is used to classify these features. This study employed a CNN to automatically extract traits from raw EMG images, which is different from conventional feature extractors. The SVM classifier then determines which hand gestures are being made. Our tests demonstrate that the proposed strategy achieves superior accuracy compared to using only CNN.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42688122","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.40915
Zirawani Baharum, Faradina Ahmad, Muhammad Imran Qureshi, D. Nasien, M. H. Adiya
The mobile-based apps used is getting popular and continued to increased. Mobile user often downloaded the apps from various sources that provided from numerous of categorization of the application included health apps. Some of apps is optional to choose, but nevertheless, there are several apps is compulsory or must-action by citizens as instructed by the government or their agency. As for that, some issues of legal challenges on data privacy kin to data security have occurred. The issues on legal challenges is more intricate for non-legal educated users with non-awareness citizens while there are government involvements. Hence, in this paper, the issues and the legal challenges on the data privacy for mobile-based application are reviewed to give awareness for both side, the users (citizens) and apps provider (government or developer). Together with that, the idea of action, such as recommendation and option to react with the issues and challenges are also presented. Several Acts (legislation) are also proposed according to the legal issues and challenges that occurred, as showed the Personal Data Protection Act (PDPA) 2010 is became as the famous act used to confront with the existing privacy legislation in mobile-based application. The suggestions and recommendations might assist citizens to keep stand with their rights on data privacy issues in mobile apps, and to the other-side, it might provide some idea be more precise when create and develop the mobile apps.
{"title":"Mobile-Based Applications: The Legal Challenges on Data Privacy","authors":"Zirawani Baharum, Faradina Ahmad, Muhammad Imran Qureshi, D. Nasien, M. H. Adiya","doi":"10.3991/ijoe.v19i09.40915","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.40915","url":null,"abstract":"The mobile-based apps used is getting popular and continued to increased. Mobile user often downloaded the apps from various sources that provided from numerous of categorization of the application included health apps. Some of apps is optional to choose, but nevertheless, there are several apps is compulsory or must-action by citizens as instructed by the government or their agency. As for that, some issues of legal challenges on data privacy kin to data security have occurred. The issues on legal challenges is more intricate for non-legal educated users with non-awareness citizens while there are government involvements. Hence, in this paper, the issues and the legal challenges on the data privacy for mobile-based application are reviewed to give awareness for both side, the users (citizens) and apps provider (government or developer). Together with that, the idea of action, such as recommendation and option to react with the issues and challenges are also presented. Several Acts (legislation) are also proposed according to the legal issues and challenges that occurred, as showed the Personal Data Protection Act (PDPA) 2010 is became as the famous act used to confront with the existing privacy legislation in mobile-based application. The suggestions and recommendations might assist citizens to keep stand with their rights on data privacy issues in mobile apps, and to the other-side, it might provide some idea be more precise when create and develop the mobile apps.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45219601","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.38147
M. S. Sadi, M. Alotaibi, Prottoy Saha, Fahamida Yeasmin Nishat, Jerin Tasnim, T. Alhmiedat, Hani Almoamari, Zaid Bassfar
With the massive outbreak of coronavirus (COVID-19) disease, the demand for automatic and quick detection of COVID-19 has become a crucial challenge for scientists around the world. Many researchers are working on finding an automated and effective system for detecting COVID-19. They have found that computed tomography (CT-scan) and X-ray images of COVID-19 infected patients can provide more accurate and faster results. In this paper, an automated system is proposed named as COV-CTX which can detect COVID-19 from CT-scan and X-ray images. The system consists of three different CNN models: VGG16, VGG16- InceptionV3-ResNet50, and Francois CNN. The models are trained with CT-scan and X-ray images individually to classify COVID-19 and non-COVID patients. Finally, the results of the models are combined to develop a voting ensemble of classifiers to ensure more accurate and precise results. The three models are trained and validated with 9412 CT-scan images (4756 numbers of COVID positive and 4656 numbers of non-COVID images) and 3257 X-ray images (1647 numbers of COVID positive and 1610 numbers of non-COVID images). The proposed system, COV-CTX provides up to 96.37% accuracy, 96.71% precision, 96.02% F1-score, 97.24% sensitivity, 95.35% specificity, 92.68% Cohens Kappa score for CT-scan image based COVID-19 detection and 99.23% accuracy, 99.37% precision, 99.22% F1-score, 99.39% sensitivity, 99.07% specificity, 98.46% Cohens Kappa score for X-ray image based COVID-19 detection.
{"title":"COV-CTX: A Deep Learning Approach to Detect COVID-19 from Lung CT and X-Ray Images","authors":"M. S. Sadi, M. Alotaibi, Prottoy Saha, Fahamida Yeasmin Nishat, Jerin Tasnim, T. Alhmiedat, Hani Almoamari, Zaid Bassfar","doi":"10.3991/ijoe.v19i09.38147","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.38147","url":null,"abstract":"With the massive outbreak of coronavirus (COVID-19) disease, the demand for automatic and quick detection of COVID-19 has become a crucial challenge for scientists around the world. Many researchers are working on finding an automated and effective system for detecting COVID-19. They have found that computed tomography (CT-scan) and X-ray images of COVID-19 infected patients can provide more accurate and faster results. In this paper, an automated system is proposed named as COV-CTX which can detect COVID-19 from CT-scan and X-ray images. The system consists of three different CNN models: VGG16, VGG16- InceptionV3-ResNet50, and Francois CNN. The models are trained with CT-scan and X-ray images individually to classify COVID-19 and non-COVID patients. Finally, the results of the models are combined to develop a voting ensemble of classifiers to ensure more accurate and precise results. The three models are trained and validated with 9412 CT-scan images (4756 numbers of COVID positive and 4656 numbers of non-COVID images) and 3257 X-ray images (1647 numbers of COVID positive and 1610 numbers of non-COVID images). The proposed system, COV-CTX provides up to 96.37% accuracy, 96.71% precision, 96.02% F1-score, 97.24% sensitivity, 95.35% specificity, 92.68% Cohens Kappa score for CT-scan image based COVID-19 detection and 99.23% accuracy, 99.37% precision, 99.22% F1-score, 99.39% sensitivity, 99.07% specificity, 98.46% Cohens Kappa score for X-ray image based COVID-19 detection.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42450951","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}
Colors are the smiles of nature. Digital image processing has widely employed the use of the function the color due to its effectiveness as a tool in classifying and identifying objects, which can be distinguished based on various relevant shades of color. This work aims to create a software tool that assists color-blind individuals in identifying the colors and edges in an image that may appear similar to them. If you are not suffering from a color vision deficiency it is very hard to imagine how it looks like to be color blind. Individuals with color blindness are limited and sometimes even disqualified from specific professions due to their inability to differentiate between colors. The objective of this research is to create a technique or approach for accurately identifying different shades of colors and predicting their names specifically for individuals with color blindness. This project utilizes image processing techniques to create a system that can recognize and distinguish colors in an image. The algorithm used for color detection in this project recognizes pixels in an image that correspond to a defined color or color range and provides the name of the color along with its corresponding B, G and R values. This work will be very helpful for people who suffer from color blindness especially when they want to know the color of the things.
{"title":"A Color Guide for Color Blind People Using Image Processing and OpenCV","authors":"P. Kompalli, Archana Kalidindi, Janakidevi Chilukala, Kumudini Nerella, Wajahath Shaik, Divija Cherukuri","doi":"10.3991/ijoe.v19i09.39177","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.39177","url":null,"abstract":"Colors are the smiles of nature. Digital image processing has widely employed the use of the function the color due to its effectiveness as a tool in classifying and identifying objects, which can be distinguished based on various relevant shades of color. This work aims to create a software tool that assists color-blind individuals in identifying the colors and edges in an image that may appear similar to them. If you are not suffering from a color vision deficiency it is very hard to imagine how it looks like to be color blind. Individuals with color blindness are limited and sometimes even disqualified from specific professions due to their inability to differentiate between colors. The objective of this research is to create a technique or approach for accurately identifying different shades of colors and predicting their names specifically for individuals with color blindness. This project utilizes image processing techniques to create a system that can recognize and distinguish colors in an image. The algorithm used for color detection in this project recognizes pixels in an image that correspond to a defined color or color range and provides the name of the color along with its corresponding B, G and R values. This work will be very helpful for people who suffer from color blindness especially when they want to know the color of the things.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44457915","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.37065
Sonu Rana, Jyoti Verma, A. Gautam
A novel miniature wideband rectangular ring antenna is proposed for 4.6–6.2 GHz which is compatible with IoT applications. The wideband response of the proposed antenna is achieved by a partial ground and stair step structure. Because modifying the width and etching the ground plane does not improve the impedance matching over a large bandwidth, a triangular shape DGS is inserted in the partial ground plane to increase the antenna bandwidth with enhanced return loss. The wideband features of the antenna were explored here by incorporating different DGS shapes such as triangles, rectangle, pentagon, circle, and oval in the partial ground. The results have been successfully verified through measurement. The simulated fractional bandwidth is greater than 29% at 4.6–6.2 GHz whereas the measured fractional bandwidth is 27.6% at 4.75–6.2 GHz. In both cases, the maximum return loss is greater than 55 dB. The gain of the antenna is greater than 2.6 dB with good efficiency and nearly omnidirectional radiation pattern in shape. Due to its compact size and outstanding performance, the suggested stair stepshaped rectangular ring antenna could be a promising choice for IoT and wireless applications.
{"title":"Design and Analysis of Wideband Stair Step-Shaped Rectangular Ring Microstrip Antenna with DGS for IoT Applications","authors":"Sonu Rana, Jyoti Verma, A. Gautam","doi":"10.3991/ijoe.v19i09.37065","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.37065","url":null,"abstract":"A novel miniature wideband rectangular ring antenna is proposed for 4.6–6.2 GHz which is compatible with IoT applications. The wideband response of the proposed antenna is achieved by a partial ground and stair step structure. Because modifying the width and etching the ground plane does not improve the impedance matching over a large bandwidth, a triangular shape DGS is inserted in the partial ground plane to increase the antenna bandwidth with enhanced return loss. The wideband features of the antenna were explored here by incorporating different DGS shapes such as triangles, rectangle, pentagon, circle, and oval in the partial ground. The results have been successfully verified through measurement. The simulated fractional bandwidth is greater than 29% at 4.6–6.2 GHz whereas the measured fractional bandwidth is 27.6% at 4.75–6.2 GHz. In both cases, the maximum return loss is greater than 55 dB. The gain of the antenna is greater than 2.6 dB with good efficiency and nearly omnidirectional radiation pattern in shape. Due to its compact size and outstanding performance, the suggested stair stepshaped rectangular ring antenna could be a promising choice for IoT and wireless applications.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43154118","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.40917
D. Novaliendry, Oktoria, Cheng-Hong Yang, Y. Desnelita, Irwan, Roni Sanjaya, Gustientiedina, Yaslinda Lizar, Noper Ardi
Hemodialysis is a procedure for cleaning the blood from the waste products of the body’s metabolism. this is one of modality to treat end stage kidney disease. There are two main classifications of this disease, namely acute kidney failure and chronic kidney failure. Kidney failure occurs when kidney damage is severe enough or lasts a long time so that the disease is generally the final stage of kidney disease. Dialysis is performed on patients with kidney failure, both acute kidney failure and chronic kidney failure. This study is aimed to predict the mortality risk of hemodialysis patients. The Taiwanese hemodialysis center enrolled a total of 665 hemodialysis patients. The prediction is based on Logistic Regression. Compared with K-Nearest Neighbor, linear discriminant, Tree, and ensemble, Logistic Regression performed better. As for related medical variables like parathyroid surgery, urea reduction ratio, etc., they play a much smaller role in mortality risk factors than diabetes and cardiovascular disease.
{"title":"Hemodialysis Patient Death Prediction Using Logistic Regression","authors":"D. Novaliendry, Oktoria, Cheng-Hong Yang, Y. Desnelita, Irwan, Roni Sanjaya, Gustientiedina, Yaslinda Lizar, Noper Ardi","doi":"10.3991/ijoe.v19i09.40917","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.40917","url":null,"abstract":"Hemodialysis is a procedure for cleaning the blood from the waste products of the body’s metabolism. this is one of modality to treat end stage kidney disease. There are two main classifications of this disease, namely acute kidney failure and chronic kidney failure. Kidney failure occurs when kidney damage is severe enough or lasts a long time so that the disease is generally the final stage of kidney disease. Dialysis is performed on patients with kidney failure, both acute kidney failure and chronic kidney failure. This study is aimed to predict the mortality risk of hemodialysis patients. The Taiwanese hemodialysis center enrolled a total of 665 hemodialysis patients. The prediction is based on Logistic Regression. Compared with K-Nearest Neighbor, linear discriminant, Tree, and ensemble, Logistic Regression performed better. As for related medical variables like parathyroid surgery, urea reduction ratio, etc., they play a much smaller role in mortality risk factors than diabetes and cardiovascular disease.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42924377","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}
Pub Date : 2023-07-07DOI: 10.3991/ijoe.v19i09.39683
H. Sadeeq, A. Abdulazeez
In science and engineering, many optimization tasks are difficult to solve, and the core concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics have gained significant attention in recent years, with nature serving as the fundamental inspiration where self-organization property led to collective intelligence emerging from the behavior of a swarm of birds or colony of insects or more and more natural behavior. These swarms or colonies, even with extremely low individual competence, have the ability to accomplish many complicated activities that can be considered necessary for their existence. Accordingly, many MH algorithms have been developed based on natural phenomena. In this article, an analysis review of more than one hundred metaheuristics have been made. Further, the main contributions of this article are to give some vital insights about metaheuristics, presenting and proposing the general mathematical framework of MH algorithms and dividing it into a number of tasks with possible progress for each task. While there are still many open issues in this field, it is worth noting that there have been significant advancements in recent years. As a result, new algorithms are continuously being proposed to address these challenges.
{"title":"Metaheuristics: A Review of Algorithms","authors":"H. Sadeeq, A. Abdulazeez","doi":"10.3991/ijoe.v19i09.39683","DOIUrl":"https://doi.org/10.3991/ijoe.v19i09.39683","url":null,"abstract":"In science and engineering, many optimization tasks are difficult to solve, and the core concern these days is to apply metaheuristic (MH) algorithms to solve them. Metaheuristics have gained significant attention in recent years, with nature serving as the fundamental inspiration where self-organization property led to collective intelligence emerging from the behavior of a swarm of birds or colony of insects or more and more natural behavior. These swarms or colonies, even with extremely low individual competence, have the ability to accomplish many complicated activities that can be considered necessary for their existence. Accordingly, many MH algorithms have been developed based on natural phenomena. In this article, an analysis review of more than one hundred metaheuristics have been made. Further, the main contributions of this article are to give some vital insights about metaheuristics, presenting and proposing the general mathematical framework of MH algorithms and dividing it into a number of tasks with possible progress for each task. While there are still many open issues in this field, it is worth noting that there have been significant advancements in recent years. As a result, new algorithms are continuously being proposed to address these challenges.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":" ","pages":""},"PeriodicalIF":1.3,"publicationDate":"2023-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48713088","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}
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