Pub Date : 2024-05-06DOI: 10.3991/ijoe.v20i07.48179
A. Zuhaida, Ari Widodo, Eka Cahya Prima, Rini Solihat
River water is essential for people’s lives and environmental health. There is a need to manage river water to maintain river water quality. This research aims to develop a river water quality analysis system that is practical, easy, and capable of storage and processing using several sensors connected to a computer system. The tools used in this research are Arduino UNO R3 board and sensors. River water samples with various characteristics were taken from four spots of the Cikapundung River. The results showed that river water quality analysis can be done using sensor-based Arduino UNO R3. The temperature at the four spots ranges from 27–32oC and is included in the safe category for sanitation use. Judging from the turbidity factor, the turbidity value of river water is in the high category, namely 49.2–58.1 NTU, which is unsuitable for sanitary use. Regarding the TDS factor, the TDS range in river water is 150–222 ppm, indicating that river water is not polluted. Meanwhile, the pH value shows that the pH range of river water is alkaline and can be used for sanitation with a range of 7.93–8.16. This indicates that the water quality in the Cikapundung River that needs attention is the turbidity factor. It takes awareness of the surrounding community and government agencies to work together to improve the river’s environmental health sustainably.
{"title":"River Water Quality Analysis Using Arduino-Based Sensor of the Cikapundung River, Indonesia","authors":"A. Zuhaida, Ari Widodo, Eka Cahya Prima, Rini Solihat","doi":"10.3991/ijoe.v20i07.48179","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.48179","url":null,"abstract":"River water is essential for people’s lives and environmental health. There is a need to manage river water to maintain river water quality. This research aims to develop a river water quality analysis system that is practical, easy, and capable of storage and processing using several sensors connected to a computer system. The tools used in this research are Arduino UNO R3 board and sensors. River water samples with various characteristics were taken from four spots of the Cikapundung River. The results showed that river water quality analysis can be done using sensor-based Arduino UNO R3. The temperature at the four spots ranges from 27–32oC and is included in the safe category for sanitation use. Judging from the turbidity factor, the turbidity value of river water is in the high category, namely 49.2–58.1 NTU, which is unsuitable for sanitary use. Regarding the TDS factor, the TDS range in river water is 150–222 ppm, indicating that river water is not polluted. Meanwhile, the pH value shows that the pH range of river water is alkaline and can be used for sanitation with a range of 7.93–8.16. This indicates that the water quality in the Cikapundung River that needs attention is the turbidity factor. It takes awareness of the surrounding community and government agencies to work together to improve the river’s environmental health sustainably.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141007481","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47373
Gabriela León, Emely López, Hans López, Cesar Hernández
Electromyographic (EMG) signals are biomedical signals that represent neuromuscular activities. The EMG signal is neither stationary nor periodic and exhibits complex interference patterns of several single motor unit action potentials (SMUAPs). This study aims to characterize EMG signals concerning firing patterns and other characteristics and to identify whether these MUAP firing patterns present short-range dependencies (SRD) or long-range dependencies (LRD). To do so, we characterized 208 EMG signals in terms of the number of phases, turns and combinations of phases. Then, we performed a statistical comparison of the (more efficient) Variance-time plot against the (less bias) Log-scale diagram for the estimation of the Hurst parameter and detection of LRD. Using these estimators, we managed to detect LRD in a sample taken with needle electrodes. In contrast, the tools used for the dependence identification on signals achieved with surface electrodes did not yield conclusive results on such dependence.
{"title":"Characterization and Identification of Dependence in EMG Signals from Action Potentials and Random Firing Patterns","authors":"Gabriela León, Emely López, Hans López, Cesar Hernández","doi":"10.3991/ijoe.v20i07.47373","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47373","url":null,"abstract":"Electromyographic (EMG) signals are biomedical signals that represent neuromuscular activities. The EMG signal is neither stationary nor periodic and exhibits complex interference patterns of several single motor unit action potentials (SMUAPs). This study aims to characterize EMG signals concerning firing patterns and other characteristics and to identify whether these MUAP firing patterns present short-range dependencies (SRD) or long-range dependencies (LRD). To do so, we characterized 208 EMG signals in terms of the number of phases, turns and combinations of phases. Then, we performed a statistical comparison of the (more efficient) Variance-time plot against the (less bias) Log-scale diagram for the estimation of the Hurst parameter and detection of LRD. Using these estimators, we managed to detect LRD in a sample taken with needle electrodes. In contrast, the tools used for the dependence identification on signals achieved with surface electrodes did not yield conclusive results on such dependence.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141007662","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47647
Jesus Orlando Gil Jauregui, Angel Gerardo Carmen Cruzatti, Miguel Angel Cano Lengua, Hugo Villaverde Medrano
Pneumonia in Peru is a very serious problem. Its impact in recent years has been aggravated due to the Covid-19 pandemic, generating an increase in infections and deaths without distinguishing the age range, which placed this country on the mortality list due to the pandemic. That is why this research seeks the causes of this problem and evaluates what patterns were detected between the years 2019–2022 in patients with pneumonia in Peru from data set from the Comprehensive Health Insurance (SIS). The data presented values related to age, gender, medication and other significant values to understand the disease. The results of the research were achieved by using the PCA technique where the dimensionality of the data was reduced from 28 to 4 main features (Patient’s year of health care, Age, BMI, Department). Finally, with this processed data set, the K-Means algorithm was used, where it was determined that patients in the 60 to 85 years range are the most affected by J189 pneumonia. In addition, an environmental pattern was found in J189 pneumonia. J128, resulting in a focus on patients on the Peruvian coast in places like Lima or La Libertad.
{"title":"Proposed Feature Selection Technique for Pattern Detection in Patients with Pneumonia Records","authors":"Jesus Orlando Gil Jauregui, Angel Gerardo Carmen Cruzatti, Miguel Angel Cano Lengua, Hugo Villaverde Medrano","doi":"10.3991/ijoe.v20i07.47647","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47647","url":null,"abstract":"Pneumonia in Peru is a very serious problem. Its impact in recent years has been aggravated due to the Covid-19 pandemic, generating an increase in infections and deaths without distinguishing the age range, which placed this country on the mortality list due to the pandemic. That is why this research seeks the causes of this problem and evaluates what patterns were detected between the years 2019–2022 in patients with pneumonia in Peru from data set from the Comprehensive Health Insurance (SIS). The data presented values related to age, gender, medication and other significant values to understand the disease. The results of the research were achieved by using the PCA technique where the dimensionality of the data was reduced from 28 to 4 main features (Patient’s year of health care, Age, BMI, Department). Finally, with this processed data set, the K-Means algorithm was used, where it was determined that patients in the 60 to 85 years range are the most affected by J189 pneumonia. In addition, an environmental pattern was found in J189 pneumonia. J128, resulting in a focus on patients on the Peruvian coast in places like Lima or La Libertad.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141010506","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47375
Gabriela León, Emely López, Hans López, Cesar Hernández
Electromyographic (EMG) signals exhibit complex interference patterns that comprise several single motor unit action potentials (SMUAPs). Evidence of a model that can generate EMG signals and considers intrinsic characteristics, such as long-range dependence (LRD) or shortrange dependence (SRD), or that supports the study of pathology-related signals is lacking. Therefore, the present study aimed to develop an EMG signal generator based on SRD or LRD derived from firing patterns. We used a dynamic model to parameterize up to 15 SMUAP waveforms of real EMG signals extracted from a database. Then, we used relative appearance rates for some signals based on the number of SMUAPs to generate the latter randomly. Furthermore, we complemented our model by generating a random firing pattern. The synthetic reconstruction of the signals indicated a displacement compared with their respective firing patterns, with the highest error rate being 4.1%. The model of the EMG signal generator in its current state could be useful for a specialist who intends to study the behavior of the signals, starting with the exploration of synthetic signals and then proceeding to the real signals.
{"title":"Design of an EMG Signal Generator Based on Random Firing Patterns","authors":"Gabriela León, Emely López, Hans López, Cesar Hernández","doi":"10.3991/ijoe.v20i07.47375","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47375","url":null,"abstract":"Electromyographic (EMG) signals exhibit complex interference patterns that comprise several single motor unit action potentials (SMUAPs). Evidence of a model that can generate EMG signals and considers intrinsic characteristics, such as long-range dependence (LRD) or shortrange dependence (SRD), or that supports the study of pathology-related signals is lacking. Therefore, the present study aimed to develop an EMG signal generator based on SRD or LRD derived from firing patterns. We used a dynamic model to parameterize up to 15 SMUAP waveforms of real EMG signals extracted from a database. Then, we used relative appearance rates for some signals based on the number of SMUAPs to generate the latter randomly. Furthermore, we complemented our model by generating a random firing pattern. The synthetic reconstruction of the signals indicated a displacement compared with their respective firing patterns, with the highest error rate being 4.1%. The model of the EMG signal generator in its current state could be useful for a specialist who intends to study the behavior of the signals, starting with the exploration of synthetic signals and then proceeding to the real signals.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141006208","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47661
F. Tsvetanov, M. Pandurski
Remote Patient Monitoring (RPM) is a healthcare solution that uses technology to monitor patients outside conventional healthcare settings. It is especially useful for people with chronic conditions or needing regular monitoring. One of the main reasons for the increase in the number of deaths each year is the increase in cardiovascular diseases, including hypertension. Online blood pressure monitoring offers many advantages but also potential challenges. This work reviews the key communication technologies and research challenges in the real-time transmission of measured blood pressure data. Delay in these systems is not tolerated as it involves human lives. To conduct the experimental studies, a prototype of an experimental intelligent system was created to study the delay and processor load of the RPI4 gateway. The measured blood pressure data is sent to the Things Board cloud using the AMQP and CoAP protocols. The experimental results are particularly useful for RPM system designers. The results of this research facilitate an informed decision on the choice of protocol that transmits the data from the gateway to the cloud in the process of designing remote patient monitoring systems.
{"title":"Delay of Transmitted Data in the Remote Patient Monitoring System through AMQP and CoAP","authors":"F. Tsvetanov, M. Pandurski","doi":"10.3991/ijoe.v20i07.47661","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47661","url":null,"abstract":"Remote Patient Monitoring (RPM) is a healthcare solution that uses technology to monitor patients outside conventional healthcare settings. It is especially useful for people with chronic conditions or needing regular monitoring. One of the main reasons for the increase in the number of deaths each year is the increase in cardiovascular diseases, including hypertension. Online blood pressure monitoring offers many advantages but also potential challenges. This work reviews the key communication technologies and research challenges in the real-time transmission of measured blood pressure data. Delay in these systems is not tolerated as it involves human lives. To conduct the experimental studies, a prototype of an experimental intelligent system was created to study the delay and processor load of the RPI4 gateway. The measured blood pressure data is sent to the Things Board cloud using the AMQP and CoAP protocols. The experimental results are particularly useful for RPM system designers. The results of this research facilitate an informed decision on the choice of protocol that transmits the data from the gateway to the cloud in the process of designing remote patient monitoring systems.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141006345","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47763
Mërgim H. Hoti, Elvir Misini, Uran Lajçi, L. Ahmedi
The application of machine learning algorithms across various fields is gaining momentum, and the results increasingly emphasize the need for further testing and implementation. This is driven by the potential to streamline and expedite numerous processes. In this paper, we have employed five algorithms: KNN, Decision Tree, Random Forest, Logistic Regression, and Naive Bayes, and these algorithms have been tested in three large datasets. On average, their performance ranges from a minimum of 80% to a maximum of 90%. Data preprocessing has been completed, and concurrently, we have implemented the SMOTE algorithm to address the challenge of unbalanced data in this research. Simultaneously, the Naïve Bayes algorithm yields the most favorable results of Accuracy, Precision, Recall, and F1 Score, for the “is_arrested” class. Furthermore, to assess the performance of each algorithm, we employed metrics including Accuracy, Precision, Recall, and F1 Score. These metrics allowed us to decide which algorithm achieved the most effective classification.
机器学习算法在各个领域的应用势头日渐强劲，其结果日益凸显出进一步测试和实施的必要性。这是因为机器学习算法具有简化和加快众多流程的潜力。在本文中，我们采用了五种算法：KNN、决策树、随机森林、逻辑回归和 Naive Bayes，并在三个大型数据集中对这些算法进行了测试。平均而言，它们的性能从最低 80% 到最高 90% 不等。数据预处理已经完成，与此同时，我们还实施了 SMOTE 算法，以应对本研究中不平衡数据的挑战。同时，对于 "is_arrested "类，Naïve Bayes 算法在准确度、精确度、召回率和 F1 分数方面都取得了最理想的结果。此外，为了评估每种算法的性能，我们采用了包括准确率、精确率、召回率和 F1 分数在内的指标。通过这些指标，我们可以确定哪种算法实现了最有效的分类。
{"title":"Machine Learning Classification Algorithms for Traffic Stops—A Comparative Study","authors":"Mërgim H. Hoti, Elvir Misini, Uran Lajçi, L. Ahmedi","doi":"10.3991/ijoe.v20i07.47763","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47763","url":null,"abstract":"The application of machine learning algorithms across various fields is gaining momentum, and the results increasingly emphasize the need for further testing and implementation. This is driven by the potential to streamline and expedite numerous processes. In this paper, we have employed five algorithms: KNN, Decision Tree, Random Forest, Logistic Regression, and Naive Bayes, and these algorithms have been tested in three large datasets. On average, their performance ranges from a minimum of 80% to a maximum of 90%. Data preprocessing has been completed, and concurrently, we have implemented the SMOTE algorithm to address the challenge of unbalanced data in this research. Simultaneously, the Naïve Bayes algorithm yields the most favorable results of Accuracy, Precision, Recall, and F1 Score, for the “is_arrested” class. Furthermore, to assess the performance of each algorithm, we employed metrics including Accuracy, Precision, Recall, and F1 Score. These metrics allowed us to decide which algorithm achieved the most effective classification.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141008082","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47827
Jaroonrut Prinyakupt, Thanakorn Yootho
The purpose of this study was to design and build a mechanical vibration assessment tool for diabetic patients’ peripheral nervous systems. There is a substantial correlation between peripheral sensory neuropathy and vibration perception threshold (VPT). Peripheral sensory neuropathy has been identified by VPT determination utilizing the VPT measurement instrument built for that purpose. The designed device can assist in determining the threshold and tracking any progressive changes or trends. This designed device consists of two main components: hardware and software. The hardware part includes a DC power supply circuit, an Arduino NANO, a display, an isolation MOSFET driver for the electrical isolation circuit, a transducer driver, and a transducer head. The software part uses C programming on the Arduino to generate signals and display the transducer supply voltage. The testing results consist of 1) the voltage settings results (5–30 volts) comparing the voltage values on the display between the designed device and a digital multimeter, which has an average error of 0.75%, 2) According to the transducer head pressing test results, the Vibrotest Digital Biothesiometer and the proposed device had different pressing weights of ±0.02 g, and 3) the electrical safety testing results of the designed device is in the standard of IEC60601-1. (IEC: International Electrotechnical Commission).
{"title":"A Design and Construction of the Vibration Perception Threshold Measurement Device for Diabetes","authors":"Jaroonrut Prinyakupt, Thanakorn Yootho","doi":"10.3991/ijoe.v20i07.47827","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47827","url":null,"abstract":"The purpose of this study was to design and build a mechanical vibration assessment tool for diabetic patients’ peripheral nervous systems. There is a substantial correlation between peripheral sensory neuropathy and vibration perception threshold (VPT). Peripheral sensory neuropathy has been identified by VPT determination utilizing the VPT measurement instrument built for that purpose. The designed device can assist in determining the threshold and tracking any progressive changes or trends. This designed device consists of two main components: hardware and software. The hardware part includes a DC power supply circuit, an Arduino NANO, a display, an isolation MOSFET driver for the electrical isolation circuit, a transducer driver, and a transducer head. The software part uses C programming on the Arduino to generate signals and display the transducer supply voltage. The testing results consist of 1) the voltage settings results (5–30 volts) comparing the voltage values on the display between the designed device and a digital multimeter, which has an average error of 0.75%, 2) According to the transducer head pressing test results, the Vibrotest Digital Biothesiometer and the proposed device had different pressing weights of ±0.02 g, and 3) the electrical safety testing results of the designed device is in the standard of IEC60601-1. (IEC: International Electrotechnical Commission).","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141010004","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47675
Muhammad Hakiki, Radinal Fadli, Arisman Sabir, Agung Prihatmojo, Yayuk Hidayah, Irwandi
This research investigates the integration of blockchain technology in vocational education in Indonesia, evaluating its impact on database system learning outcomes. Involving 86 Indonesian students, this study aims to assess the effectiveness of blockchain in improving students’ understanding, skills, and academic performance. Using a quasi-experimental design, the findings of this study showed a significant improvement in learning outcomes, as evidenced by the analysis of pre-test and post-test scores. The measure of the effectiveness of the improvement in learning outcomes, with a substantial increase of approximately 46.50%, emphasizes the positive influence of blockchain technology on student achievement in the database systems course. The findings of this study will contribute valuable information to educational institutions, policy makers, and educators who wish to incorporate new technologies such as blockchain into their learning systems. The implication of this research is to provide recommendations in optimizing the integration of blockchain technology, which significantly affects learning outcomes in database systems. This is realized through facilitating fast and efficient access to learning materials, fostering a more interactive and engaging learning environment, and enhancing students’ understanding of industry practices. The integration of blockchain into database systems learning not only improves the quality of learning but also equips students for a successful career in information technology.
{"title":"The Impact of Blockchain Technology Effectiveness in Indonesia's Learning System","authors":"Muhammad Hakiki, Radinal Fadli, Arisman Sabir, Agung Prihatmojo, Yayuk Hidayah, Irwandi","doi":"10.3991/ijoe.v20i07.47675","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47675","url":null,"abstract":"This research investigates the integration of blockchain technology in vocational education in Indonesia, evaluating its impact on database system learning outcomes. Involving 86 Indonesian students, this study aims to assess the effectiveness of blockchain in improving students’ understanding, skills, and academic performance. Using a quasi-experimental design, the findings of this study showed a significant improvement in learning outcomes, as evidenced by the analysis of pre-test and post-test scores. The measure of the effectiveness of the improvement in learning outcomes, with a substantial increase of approximately 46.50%, emphasizes the positive influence of blockchain technology on student achievement in the database systems course. The findings of this study will contribute valuable information to educational institutions, policy makers, and educators who wish to incorporate new technologies such as blockchain into their learning systems. The implication of this research is to provide recommendations in optimizing the integration of blockchain technology, which significantly affects learning outcomes in database systems. This is realized through facilitating fast and efficient access to learning materials, fostering a more interactive and engaging learning environment, and enhancing students’ understanding of industry practices. The integration of blockchain into database systems learning not only improves the quality of learning but also equips students for a successful career in information technology.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141009002","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 : 2024-05-06DOI: 10.3991/ijoe.v20i07.47803
Mohammed Waly
In the realm of healthcare administration, heightened expectations can lead to stress, therefore impacting working conditions. Specifically, studies on leadership styles have provided a valuable understanding of the factors that hinder performance, particularly in relation to the implementation of transactional leadership. Despite its crucial significance, there is a dearth of research on the management styles employed in clinical engineering. This study examines the impact of leadership styles on the functioning of medical equipment. We assess leadership styles and the performance of medical equipment from the perspective of end-users using a cross-sectional survey and questionnaires that consider many significant criteria. A neural network model is employed to classify the leadership styles exhibited by the Clinical Engineering Department (CED) and to analyze the correlation between these styles and the equipment’s performance. The results suggest a significant correlation between the leadership styles of those in charge of CED and the functioning of medical equipment. A strong and favorable correlation exists between transformative leadership and equipment performance (r = 0.856**, P = 0.000). The data suggests that transformative leadership is highly significant, with a mean score of 3.07 ± 0.817.
{"title":"Examining the Relation of Transformational Leadership in Clinical Engineering on the Performance of Medical Equipment: A Neural Network Approach","authors":"Mohammed Waly","doi":"10.3991/ijoe.v20i07.47803","DOIUrl":"https://doi.org/10.3991/ijoe.v20i07.47803","url":null,"abstract":"In the realm of healthcare administration, heightened expectations can lead to stress, therefore impacting working conditions. Specifically, studies on leadership styles have provided a valuable understanding of the factors that hinder performance, particularly in relation to the implementation of transactional leadership. Despite its crucial significance, there is a dearth of research on the management styles employed in clinical engineering. This study examines the impact of leadership styles on the functioning of medical equipment. We assess leadership styles and the performance of medical equipment from the perspective of end-users using a cross-sectional survey and questionnaires that consider many significant criteria. A neural network model is employed to classify the leadership styles exhibited by the Clinical Engineering Department (CED) and to analyze the correlation between these styles and the equipment’s performance. The results suggest a significant correlation between the leadership styles of those in charge of CED and the functioning of medical equipment. A strong and favorable correlation exists between transformative leadership and equipment performance (r = 0.856**, P = 0.000). The data suggests that transformative leadership is highly significant, with a mean score of 3.07 ± 0.817.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141008305","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 : 2024-04-12DOI: 10.3991/ijoe.v20i06.46979
Sobha Xavier P, Sathish P K, Raju G
Accurate segmentation of brain tumors is vital for effective treatment planning, disease diagnosis, and monitoring treatment outcomes. Post-surgical monitoring, particularly for recurring tumors, relies on MRI scans, presenting challenges in segmenting small residual tumors due to surgical artifacts. This emphasizes the need for a robust model with superior feature extraction capabilities for precise segmentation in both pre- and post-operative scenarios. The study introduces the Hybrid Attention-Residual UNET with Transformer Blocks (HART-UNet), enhancing the U-Net architecture with a spatial self-attention module, deep residual connections, and RESNET50 weights. Trained on BRATS’20 and validated on Kaggle LGG and BTC_ postop datasets, HART-UNet outperforms established models (UNET, Attention UNET, UNET++, and RESNET 50), achieving Dice Coefficients of 0.96, 0.97, and 0.88, respectively. These results underscore the model’s superior segmentation performance, marking a significant advancement in brain tumor analysis across pre- and post-operative MRI scans.
{"title":"Advancing Brain Tumor Segmentation in MRI Scans: Hybrid Attention-Residual UNET with Transformer Blocks","authors":"Sobha Xavier P, Sathish P K, Raju G","doi":"10.3991/ijoe.v20i06.46979","DOIUrl":"https://doi.org/10.3991/ijoe.v20i06.46979","url":null,"abstract":"Accurate segmentation of brain tumors is vital for effective treatment planning, disease diagnosis, and monitoring treatment outcomes. Post-surgical monitoring, particularly for recurring tumors, relies on MRI scans, presenting challenges in segmenting small residual tumors due to surgical artifacts. This emphasizes the need for a robust model with superior feature extraction capabilities for precise segmentation in both pre- and post-operative scenarios. The study introduces the Hybrid Attention-Residual UNET with Transformer Blocks (HART-UNet), enhancing the U-Net architecture with a spatial self-attention module, deep residual connections, and RESNET50 weights. Trained on BRATS’20 and validated on Kaggle LGG and BTC_ postop datasets, HART-UNet outperforms established models (UNET, Attention UNET, UNET++, and RESNET 50), achieving Dice Coefficients of 0.96, 0.97, and 0.88, respectively. These results underscore the model’s superior segmentation performance, marking a significant advancement in brain tumor analysis across pre- and post-operative MRI scans.","PeriodicalId":507997,"journal":{"name":"International Journal of Online and Biomedical Engineering (iJOE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140709267","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：