International Journal of Online and Biomedical Engineering最新文献_第9页

Applying Optimized Algorithms and Technology for Interconnecting Big Data Resources in Government Institutions 优化算法与技术在政府机构大数据资源互联中的应用

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.39661

Genc Hamzaj, Artan Mazrekaj, Isak Shabani

{"title":"Applying Optimized Algorithms and Technology for Interconnecting Big Data Resources in Government Institutions","authors":"Genc Hamzaj, Artan Mazrekaj, Isak Shabani","doi":"10.3991/ijoe.v19i08.39661","DOIUrl":"https://doi.org/10.3991/ijoe.v19i08.39661","url":null,"abstract":"The quality of the data in core electronic registers has constantly decreased as a result of numerous errors that were made and inconsistencies in the data in these databases due to the growing number of databases created with the intention of providing electronic services for public administration and the lack of the data harmonization or interoperability between these databases.Evaluating and improving the quality of data by matching and linking records from multiple data sources becomes exceedingly difficult due to the incredibly large volume of data in these numerous data sources with different data architectures and no unique field to create interconnection among them.Different algorithms are developed to treat these issues and our focus will be on algorithms that handle large amounts of data, such as Levenshtein distance (LV) algorithm and Damerau-Levenshtein distance (DL) algorithm.In order to analyze and evaluate the effectiveness and quality of data using the mentioned algorithms and making improvements to these algorithms, through this paper we will conduct experiments on large data sets with more than 1 million records.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47827407","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

Comparative Simulation Study of Classical and Machine Learning Techniques for Forecasting Time Series Data 时间序列数据预测的经典与机器学习技术对比仿真研究

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.39853

M’barek Iaousse, Youness Jouilil, Mohamed Bouincha, D. Mentagui

引用次数: 4

Design of an Adaptive State Anesthesia Feedback Controller 自适应状态麻醉反馈控制器的设计

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.39881

Faten Imad Ali, Mais Al-Saffar, Noor Ali Sadek

引用次数: 0

Machine Learning Based Improved Heart Disease Detection with Confidence 基于机器学习的改进心脏病检测的信心

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.37417

Anas Domyati, Q. Memon

引用次数: 0

Smartphone-Based Wearable Gait Monitoring System Using Wireless Inertial Sensors 基于智能手机的可穿戴式无线惯性传感器步态监测系统

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.38781

Alejandro Astudillo, Edna Avella-Rodríguez, Gloria Arango-Hoyos, J. Ramirez-Scarpetta, Esteban Rosero

{"title":"Smartphone-Based Wearable Gait Monitoring System Using Wireless Inertial Sensors","authors":"Alejandro Astudillo, Edna Avella-Rodríguez, Gloria Arango-Hoyos, J. Ramirez-Scarpetta, Esteban Rosero","doi":"10.3991/ijoe.v19i08.38781","DOIUrl":"https://doi.org/10.3991/ijoe.v19i08.38781","url":null,"abstract":"This paper presents a wearable virtual reality system with a wireless network of inertial sensors for lower limb monitoring. The system comprises seven sensor nodes sending data wirelessly to a master node. The information is then collected, organized, and sent to a screening device via a serial interface. An application executed either on a smartphone or a personal computer features an avatar which represents the received data and mimics the sensed movements of the patient, providing online feedback during and after the execution of a therapy. The data resulting from the therapy execution can be uploaded to a web server to facilitate the assessment and decision-making by health professionals. A pendulum featuring a rotary optical encoder is used for sensor functional behavior validation. In addition, the orientation angles measured by the proposed system are compared with respect to measurements from the motion analysis software Kinovea. The delay between the patient's body movement and the avatar is 33 ms, which is acceptable for visual feedback. This system is portable, inexpensive and enables a patient to complete physical therapy sessions at home or anywhere, with the advantage of enabling visual feedback through an avatar during rehabilitation therapy and allowing the reproduction of a therapy session for further analysis.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42227247","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

The Evolution and Reliability of Machine Learning Techniques for Oncology 肿瘤学机器学习技术的发展和可靠性

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-27 DOI: 10.3991/ijoe.v19i08.39433

Hamza Abu Owida, Bashar Al-haj Moh'd, Nidal M. Turab, J. Al-Nabulsi, Suhaila Abuowaida

{"title":"The Evolution and Reliability of Machine Learning Techniques for Oncology","authors":"Hamza Abu Owida, Bashar Al-haj Moh'd, Nidal M. Turab, J. Al-Nabulsi, Suhaila Abuowaida","doi":"10.3991/ijoe.v19i08.39433","DOIUrl":"https://doi.org/10.3991/ijoe.v19i08.39433","url":null,"abstract":"It is no secret that the rise of the Internet and other digital technologies has sparked renewed interest in AI-based techniques, especially those that fall under the umbrella of the subset of algorithms known as \"Machine Learning\" (ML). \u0000These advancements in electronics have allowed us to comprehend the world beyond the bounds of human cognition. A high-dimensional dataset's complicated nature. Although these techniques have been regularly employed by the medical sciences, their adoption to enhance patient care has been a bit slow. The availability of curated diverse data sets for model development is all examples of the substantial hurdles that have delayed these efforts. The future clinical acceptance of each of these characteristics may be affected by a number of limiting conditions, such as the time and resources spent on data collection and model development, the cost of integration relative to the time and resources spent on translation, and the potential for patient damage. In order to preserve value and enhance medical care, the goal of this article is to evaluate all facets of the issue in light of the validity of using ML methods in cancer, to serve as a template for further research and the subfield of oncology that serves as a model for other parts of the discipline.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44990808","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

A Convolution Neural Network Design for Knee Osteoarthritis Diagnosis Using X-ray Images 利用X射线图像诊断膝关节骨性关节炎的卷积神经网络设计

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-13 DOI: 10.3991/ijoe.v19i07.40161

Saleh Hamad Sajaan Almansour, Rahul Singh, S. M. Alyami, N. Sharma, Mana Saleh Al Reshan, Sheifali Gupta, Mahdi Falah Mahdi Alyami, A. Shaikh

{"title":"A Convolution Neural Network Design for Knee Osteoarthritis Diagnosis Using X-ray Images","authors":"Saleh Hamad Sajaan Almansour, Rahul Singh, S. M. Alyami, N. Sharma, Mana Saleh Al Reshan, Sheifali Gupta, Mahdi Falah Mahdi Alyami, A. Shaikh","doi":"10.3991/ijoe.v19i07.40161","DOIUrl":"https://doi.org/10.3991/ijoe.v19i07.40161","url":null,"abstract":"Knee osteoarthritis (OA) is a chronic degenerative joint disease affecting millions worldwide, particularly those over 60. It is a significant cause of disability and can impact an individual's quality of life. The condition occurs when the cartilage in the knee joint wears away over time, leading to bone-on-bone contact, which can result in pain, stiffness, swelling, and decreased range of motion. Deep neural networks, especially convolutional neural networks (CNN), are powerful tools in medical applications such as diagnosis and detection. This research proposes a CNN model to classify knee osteoarthritis into five categories using x-ray images. These classes are labeled: Minimal, Healthy, Moderate, Doubtful, and Severe. Furthermore, the proposed CNN model has been compared with two pre-trained transfer learning models: Xception and InceptionResNet V2. These models were evaluated based on precision, recall, F1 score, and accuracy. The results showed that although all three models performed very well, the proposed model outperformed both transfer learning models with 98% accuracy. It also achieved the highest values for other parameters such as precision, recall, and F1 score. The proposed model has several potential applications in clinical practice, such as assisting doctors in accurately classifying knee osteoarthritis severity levels by analyzing single X-ray images.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48386574","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

Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol 基于实时传输协议的触觉数据传输仿真框架

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-13 DOI: 10.3991/ijoe.v19i07.39187

Israa Abdullah, Wrya Monnet

{"title":"Emulation Framework for Haptic Data Transmission Using Real-Time Transport Protocol","authors":"Israa Abdullah, Wrya Monnet","doi":"10.3991/ijoe.v19i07.39187","DOIUrl":"https://doi.org/10.3991/ijoe.v19i07.39187","url":null,"abstract":"The Tactile Internet (TI) can be regarded as the next evolution in the world of communication. With its envisioned purpose and potential in shaping up the economy, industry and society, this paradigm aims to bring a new dimension to life by enabling humans to interact with machines remotely and in real-time with haptic and kinesthetic feedback. However, to translate this into reality, Tactile Internet will need to meet the stringent requirements of extremely low latency in conjunction with ultra-high reliability, availability, and security. This poses a challenge on the available communication systems to achieve a round-trip delay within 1 to 10 milliseconds time bound that enables the timely delivery of critical tactile and haptic sensations. \u0000This paper aims to evaluate the Real-Time Transport Protocol (RTP) through an emulation framework. It integrates containerization using Linux-based Docker Containers with NS-3 Network Simulator to conceptualize a haptic teleoperation system. The framework is then used to test the protocol’s feasibility for delivering texture haptic data between master and slave domains in accordance with the end-to-end delay requirements specified by IEEE 1918.1 standards. The results have shown that the timely provision of haptic data is achievable by obtaining an average round-trip delay of 17.8493 ms from the emulation experiment. As such, the results satisfy the expected IEEE 1918.1 standards constraints for medium-dynamic environment use cases.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47036755","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

Localization of Strangeness for Real Time Video in Crowd Activity Using Optical Flow and Entropy 基于光流和熵的人群活动实时视频陌生度定位

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-13 DOI: 10.3991/ijoe.v19i07.38869

Ali Abid Hussan Altalbi, Shaimaa Hameed Shaker, Akbas Ezaldeen Ali

{"title":"Localization of Strangeness for Real Time Video in Crowd Activity Using Optical Flow and Entropy","authors":"Ali Abid Hussan Altalbi, Shaimaa Hameed Shaker, Akbas Ezaldeen Ali","doi":"10.3991/ijoe.v19i07.38869","DOIUrl":"https://doi.org/10.3991/ijoe.v19i07.38869","url":null,"abstract":"Anomaly detection, which is also referred to as novelty detection or outlier detection, is process of identifying unusual occurrences, observations, or events which considerably differ from the bulk of data and do not fit a predetermined definition of typical behavior. Medicine, cybersecurity, statistics, machine vision, law enforcement, neurology, and financial fraud are just a handful of the industries where anomaly detection is used. In the presented study, an online tool is utilized to identify crowd distortions, which could be brought on by panic. An activity map is produced with the use of numerous frames to show the continuity regarding the flow over time following the global optical flow has been calculated in the quickest time and with the highest precision possible utilizing the Farneback approach to calculate the magnitudes. Utilizing a specific threshold, the oddity in the video will be picked up by the activity map's generation of an entropy. The results indicate that the maximum entropy level for indoor video is <0.16 and the maximum entropy level for outdoor video is >0.45. A threshold of 0.04 is used to determine whether a frame is abnormal or normal.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44852497","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

Time Series Analysis with Systematic Survey on Covid-19 Based Predictive Studies During Pandemic Period using Enhanced Machine Learning Techniques 利用增强的机器学习技术对新冠肺炎大流行期间基于预测研究的时间序列分析和系统调查

IF 1.3

International Journal of Online and Biomedical Engineering Pub Date : 2023-06-13 DOI: 10.3991/ijoe.v19i07.39089

K. Rajeswari, Sushma Vispute, Amulya Maitre, Reena Kharat, Amruta Aher, N. Vivekanandan, Renu Kachoria, Swati Jaiswal

{"title":"Time Series Analysis with Systematic Survey on Covid-19 Based Predictive Studies During Pandemic Period using Enhanced Machine Learning Techniques","authors":"K. Rajeswari, Sushma Vispute, Amulya Maitre, Reena Kharat, Amruta Aher, N. Vivekanandan, Renu Kachoria, Swati Jaiswal","doi":"10.3991/ijoe.v19i07.39089","DOIUrl":"https://doi.org/10.3991/ijoe.v19i07.39089","url":null,"abstract":"Coronavirus 2 virus is responsible for the spread of the infectious disease COVID-19 (also known as Coronavirus disease). People around the globe who got infected with the virus experienced a respiratory illness that could become as serious as leading someone to lose their life. However, the upside of the pandemic is that it has led to numerous types of research and explorations, majorly in the medical science field. Since a systematic survey of previous research activities and bibliometric analysis gives a brief idea about such contributions and acts as a reference to future research, this study aims to cover the research related to COVID-19 in the computer technology domain. It is limited to the works accepted and accessible with the keywords - Covid-19, prediction, and pandemic, in the Scopus search engine to justify the scope of this survey. Further, the paper highlights a few prior works used for predictive analysis and presents a quantitative angle on their algorithms. Earlier works showcase Time Series Analysis using ARIMA/SARIMA models for predicting the vaccination rates, and Extreme Gradient Boosting (XGBoost), Xtremely Boosted Network (XBNet) Regression, and Recurrent Neural Network (RNN) for Confirmed, Cured, and Death cases. Amongst the algorithms used in the latter use case, XBNet regression performed better than XGBoost regressor.","PeriodicalId":36900,"journal":{"name":"International Journal of Online and Biomedical Engineering","volume":null,"pages":null},"PeriodicalIF":1.3,"publicationDate":"2023-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49646148","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