Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (9298)
- Physical Sciences and Mathematics (6664)
- Social and Behavioral Sciences (4016)
- Medicine and Health Sciences (3666)
- Life Sciences (3063)
-
- Education (3012)
- Computer Sciences (2747)
- Arts and Humanities (2533)
- Civil and Environmental Engineering (1805)
- Law (1800)
- Business (1388)
- Electrical and Computer Engineering (1342)
- Mechanical Engineering (1322)
- Computer Engineering (1294)
- Medical Specialties (1236)
- Environmental Sciences (1201)
- Medical Sciences (1141)
- Artificial Intelligence and Robotics (1063)
- Materials Science and Engineering (1003)
- Higher Education (995)
- Public Affairs, Public Policy and Public Administration (804)
- Chemical Engineering (768)
- Earth Sciences (709)
- Architecture (678)
- Operations Research, Systems Engineering and Industrial Engineering (670)
- Chemistry (665)
- Biomedical Informatics (637)
- Physics (600)
- Biomedical Engineering and Bioengineering (596)
- Bioinformatics (567)
- Institution
-
- University of South Florida (1150)
- The Texas Medical Center Library (1095)
- Missouri University of Science and Technology (840)
- New Jersey Institute of Technology (834)
- Chulalongkorn University (796)
-
- Changsha University of Science and Technology (773)
- Utah State University (706)
- Purdue University (681)
- Singapore Management University (660)
- University of Kentucky (659)
- Walden University (585)
- University of Nebraska - Lincoln (570)
- University of Arkansas, Fayetteville (549)
- California Polytechnic State University, San Luis Obispo (508)
- San Jose State University (502)
- University of New Mexico (494)
- Louisiana State University (487)
- University of New Hampshire (463)
- Old Dominion University (431)
- University of Plymouth (430)
- Brigham Young University (406)
- Portland State University (405)
- University of Texas Rio Grande Valley (387)
- Liberty University (358)
- Clemson University (355)
- Association of Arab Universities (349)
- Kennesaw State University (349)
- University of South Carolina (343)
- Embry-Riddle Aeronautical University (320)
- Washington University in St. Louis (319)
- Keyword
-
- Humans (912)
- Machine learning (504)
- Animals (476)
- Artificial intelligence (374)
- Undergraduate (357)
-
- Mice (332)
- Female (314)
- Machine Learning (298)
- Male (277)
- Deep learning (270)
- Artificial Intelligence (253)
- Sustainability (229)
- Education (207)
- AI (194)
- Climate change (186)
- ICTS (Institute of Clinical and Translational Sciences) (186)
- Mechanical and Industrial Engineering (172)
- Higher education (169)
- COVID-19 (163)
- Technology (159)
- Deep Learning (156)
- Mechanical Engineering (156)
- Mathematics (152)
- Face to Face (150)
- 300-level (143)
- Engineering (141)
- Adult (131)
- Optimization (128)
- Middle Aged (125)
- Cybersecurity (123)
- Publication
-
- Theses and Dissertations (1462)
- Faculty, Staff and Student Publications (685)
- Faculty Publications (621)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (562)
- Walden Dissertations and Doctoral Studies (561)
-
- Research Collection School Of Computing and Information Systems (480)
- The Auk (473)
- Journal of China & Foreign Highway (392)
- Theses (364)
- Electronic Theses and Dissertations (363)
- Dissertations (327)
- Faculty, Staff and Students Publications (300)
- Research outputs 2022 to 2026 (284)
- DRS Biennial Conference Series (263)
- Faculty Scholarship (255)
- Defensive Publications Series (252)
- Doctoral Dissertations and Projects (252)
- Neutrosophic Sets and Systems (250)
- Journal of System Simulation (242)
- Coal Geology & Exploration (231)
- Master's Theses (230)
- 2020-Current year OA Pubs (225)
- Food and Machinery (214)
- Bulletin of Chinese Academy of Sciences (Chinese Version) (184)
- All Dissertations (179)
- USF Tampa Graduate Theses and Dissertations (177)
- Small Satellite Conference (175)
- Mechanical and Industrial Engineering Syllabi (172)
- Articles (170)
- Journal of Engineering Research (169)
- Publication Type
Articles 39121 - 39135 of 39135
Full-Text Articles in Entire DC Network
Machine Learning Helps In Quickly Diagnosis Cases Of "New Corona", Maad M. Mijwil, Ioannis Adamopoulos, Pramila Pudasaini
Machine Learning Helps In Quickly Diagnosis Cases Of "New Corona", Maad M. Mijwil, Ioannis Adamopoulos, Pramila Pudasaini
Mesopotamian Journal of Artificial Intelligence in Healthcare
Machine learning is considered one of the most significant techniques that play a vital role in diagnosing the Coronavirus. It is a set of advanced algorithms capable of analysing medical data and identifying patterns and behaviours of diseases. It is used to interpret medical images, giving details of each image with high accuracy and efficiency, such as chest X-ray images. These algorithms are trained on a large set of images to recognise patterns that indicate the presence of infection with the Coronavirus (COVID-19). This article will provide a brief overview of the importance of machine learning in diagnosing COVID-19 by …
Exploring Deep Learning Methods Used In The Medical Device Sector, Fredrick Kayusi, Benson Turyasingura, Petros Chavula, Orucho Justine Amadi
Exploring Deep Learning Methods Used In The Medical Device Sector, Fredrick Kayusi, Benson Turyasingura, Petros Chavula, Orucho Justine Amadi
Mesopotamian Journal of Artificial Intelligence in Healthcare
The healthcare sector is witnessing significant development in many aspects thanks to the effects of artificial intelligence or software, which has turned out to be the centre of attraction all over the world. This is evidence of a simple development in acquiring deep knowledge of the methods and areas in which they are used. Face detection, voice recognition, autonomous use, the defence industry, the security industry, and other fields may be displayed as examples that help complete tasks. This article surveys the impact of deep learning methods and practices in the medical device industry, and we also examine the distribution …
Machine Learning Based Lung Disease Prediction Using Convolutional Neural Network Algorithm, M. Sahaya Sheela, G. Amirthayogam, J. Jasmine Hephzipah, S. Gopalakrishnan, S. Ravi Chand
Machine Learning Based Lung Disease Prediction Using Convolutional Neural Network Algorithm, M. Sahaya Sheela, G. Amirthayogam, J. Jasmine Hephzipah, S. Gopalakrishnan, S. Ravi Chand
Mesopotamian Journal of Artificial Intelligence in Healthcare
Lung disease prediction is a critical issue in today's world. However, in the past two years, the corona virus disease 2019 (COVID-19) has a broad range and, in a limited percentage of people, a notable effect on the lungs. In the past, the fuzzy logic method has been used to classify lung disease prediction, but it has faced challenges such as difficulties in identifying segmented regions and output inaccuracies. To solve the issue Convolutional neural networks are used in machine learning to predict lung condition. The preprocessing based weighted average filter gives greater weight to the central value, making its …
Assigning Medical Professionals: Chatgpt's Contributions To Medical Education And Health Prediction, Maad M. Mijwil, Mostafa Abotaleb, Guma Ali, Klodian Dhoska
Assigning Medical Professionals: Chatgpt's Contributions To Medical Education And Health Prediction, Maad M. Mijwil, Mostafa Abotaleb, Guma Ali, Klodian Dhoska
Mesopotamian Journal of Artificial Intelligence in Healthcare
Artificial intelligence is increasingly present in many applications that help humans accomplish many tasks. It can support improved results, increased productivity, and high efficiency in providing services. Systems developers seek to integrate improved artificial intelligence models into the development of healthcare services and make a significant qualitative shift in the medical field. One recently invented tool is ChatGPT, which deserves extensive advertising space. This tool provides sample answers that help both healthcare workers and patients answer all their questions. It is an important tool in medical education, increasing knowledge in making decisions that can improve the performance of medical professionals. …
Iot Revolutionizes Humidity Measurement And Management In Smart Cities To Enhance Health And Wellness, Pushan Kumar Dutta, Bhupinder Singh, Al-Sayed K. Towfeek, Jovanna Pantelis Adamopoulou, Antonis Nikos Bardavouras, Wilson Bamwerinde, Benson Turyasingura, Natal Ayiga
Iot Revolutionizes Humidity Measurement And Management In Smart Cities To Enhance Health And Wellness, Pushan Kumar Dutta, Bhupinder Singh, Al-Sayed K. Towfeek, Jovanna Pantelis Adamopoulou, Antonis Nikos Bardavouras, Wilson Bamwerinde, Benson Turyasingura, Natal Ayiga
Mesopotamian Journal of Artificial Intelligence in Healthcare
This paper sets itself in a context of examining how IoT technology is disrupting and revolutionizing the monitoring and control of relative humidity in different spheres of smart cities with special reference to the enhancement of well-being in the information society. The authors discuss the current emergent research topics in IoT-based humidity sensors, wireless communication systems, and big data analytics for monitoring and controlling the humidity in real time. The paper also presents an outlook into various fields such as agriculture, healthcare, intelligent houses, industries, as well as the environment, and presents an indication of how managing humidity accurately enhances …
Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi
Machine Learning Techniques To Predictive In Healthcare: Hepatitis C Diagnosis, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi
Mesopotamian Journal of Artificial Intelligence in Healthcare
The accurate prediction and classification of medical data, such as Hepatitis C, play a significant role in upgrading symptomatic accuracy and treatment planning. This study utilized progressed machine learning algorithms, including RF, SVR, and Gradient Boosting, to analyze features and predict outcomes viably. By coordination robust preprocessing strategies and feature engineering, the models tended to missing values and categorical transformations, enabling exact predictions from complex datasets. The models accomplished high accuracy and unwavering quality in execution, as prove by comparative measurements and validation results. These discoveries highlight the potential of machine learning in increasing clinical decision-making and emphasize the require …
Hybrid Model Approaches For Accurate Time Series Predicting Of Covid-19 Cases, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Benson Turyasingura
Hybrid Model Approaches For Accurate Time Series Predicting Of Covid-19 Cases, Hussein Alkattan, Bashar Talib Al-Nuaimi, Alhumaima Ali Subhi, Benson Turyasingura
Mesopotamian Journal of Artificial Intelligence in Healthcare
This study compares the performance of ARIMA, LSTM, and hybrid models in predicting COVID-19 cases and analyzing forecast errors. Utilizing real-world data, the models were assessed for accuracy and trend prediction over numerous months. Heatmaps of prediction errors revealed that the hybrid model reliably outperformed ARIMA and LSTM by accomplishing lower error extents. The findings highlight the preferences of combining statistical and deep learning approaches for time series predicting. The results contribute to progressing predicting accuracy, which is basic for pandemic response arranging and public health administration.
An Extensive Examination Of The Iot And Blockchain Technologies In Relation To Their Applications In The Healthcare Industry, Karthik Kumar Vaigandla, Madhu Kumar Vanteru, Mounika Siluveru
An Extensive Examination Of The Iot And Blockchain Technologies In Relation To Their Applications In The Healthcare Industry, Karthik Kumar Vaigandla, Madhu Kumar Vanteru, Mounika Siluveru
Mesopotamian Journal of Computer Science
Numerous domains have been transformed by the communication technologies made possible by the Internet of Things (IoT), one of which is health monitoring systems. Patterns associated with diseases and health conditions can be identified through the utilization of machine learning and cutting-edge AI techniques. Currently, scientific endeavours are concentrated on enhancing IoT-enabled applications such as medical report administration, prescription traceability, and infectious disease surveillance through the amalgamation of blockchain technology(BCT) and machine learning(ML) models. Although recent advancements have attempted to increase the adaptability of blockchain(BC) and ML for IoT applications, there are still a number of crucial considerations that must …
Generative Artificial Intelligence And Cybersecurity Risks: Implications For Healthcare Security Based On Real-Life Incidents, Malik Sallam, Kholoud Al-Mahzoum, Mohammed Sallam
Generative Artificial Intelligence And Cybersecurity Risks: Implications For Healthcare Security Based On Real-Life Incidents, Malik Sallam, Kholoud Al-Mahzoum, Mohammed Sallam
Mesopotamian Journal of Artificial Intelligence in Healthcare
Background: The potential of generative artificial intelligence (genAI) tools, such as ChatGPT, is being increasingly explored in healthcare settings. However, the same tools also introduce significant cybersecurity risks that could compromise patient safety, data integrity, and institutional trust. This study aimed to examine real-world security breaches involving genAI and extrapolate their potential implications for healthcare settings. Methods: Using a systematic Google News search and a consensus-based approach among the authors, five high-profile genAI breaches were identified and analyzed. These cases included: (1) Data exposure in ChatGPT (OpenAI) due to an open-source library bug (March 2023); (2) Unauthorized data disclosure via …
A Comparative Study Of Chest Radiographs And Detection Of The Covid 19 Virus Using Machine Learning Algorithm, Shaimaa Q. Sabri, Jahwar Y. Arif, Ghada A. Taqa, Ahmet Çınar
A Comparative Study Of Chest Radiographs And Detection Of The Covid 19 Virus Using Machine Learning Algorithm, Shaimaa Q. Sabri, Jahwar Y. Arif, Ghada A. Taqa, Ahmet Çınar
Mesopotamian Journal of Computer Science
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak that is causing coronavirus disease 2019 is being deemed a pandemic because of its quick spread around the globe. Because chest X-ray pictures have shown to be beneficial in monitoring a variety of lung disorders, they have recently been utilized to monitor COVID-19 disease. It takes time to manually analyze a lot of chest X-ray pictures. Several previous studies have suggested machine-learning (ML)-based techniques for COVID-19 detection from chest X-ray pictures as a solution to this issue. Though little effort has been made to use traditional machine learning (ML) methods, the …
Introduction To Wi-Fi 7: A Review Of History, Applications, Challenges, Economical Impact And Research Development, Sallar Salam Murad, Rozin Badeel, Banan Badeel Abdal, Tasmeea Rahman, Tahsien Al-Quraishi
Introduction To Wi-Fi 7: A Review Of History, Applications, Challenges, Economical Impact And Research Development, Sallar Salam Murad, Rozin Badeel, Banan Badeel Abdal, Tasmeea Rahman, Tahsien Al-Quraishi
Mesopotamian Journal of Computer Science
Wi-Fi 7, commonly referred to as IEEE 802.11be, is the most recent development in wireless communication technology. It provides significant improvements in terms of speed, capacity, and efficiency. The purpose of this study is to investigate Wi-Fi 7, a standard for wireless communication technology, with a particular focus on the technological advancements and security issues associated with it. In addition, it offers historical perspectives and investigates the institution's present capabilities as well as its potential for the future. The purpose of this study is to provide a complete examination of the development of Wi-Fi technology and its influence on a …
Deep Learning Model For Hand Movement Rehabilitation, Reem D. Ismail, Qabas A. Hameed, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Fatimah N. Ameen
Deep Learning Model For Hand Movement Rehabilitation, Reem D. Ismail, Qabas A. Hameed, Mustafa Abdulfattah Habeeb, Yahya Layth Khaleel, Fatimah N. Ameen
Mesopotamian Journal of Computer Science
Electroencephalography (EEG) can control machines for human purposes, especially for disabled people doing rehabilitation exercises or regular tasks. Brain-computer interface (BCI) for Robotic hand uses deep learning to convert (EEG) brain activity into orders for robotic hand allowing users to move their hands right or left by the movement imagining. It could enable paralyzed individuals to perform basic hand movements and help in rehabilitation robots that help stroke patients regain hand function by offering guided exercises based on machine learning interpretations of their movements and intents. Artificial intelligence algorithms, particularly deep learning, classify and recognize patterns and intents implicit brainwaves …
Potato Disease Identification Using Transfer Learning Approaches, Tarza Hasan Abdullah
Potato Disease Identification Using Transfer Learning Approaches, Tarza Hasan Abdullah
Mesopotamian Journal of Computer Science
Potato crop is one of the prominent consumed foods by human beings. When potato crops are infected by diseases it affects farmers negatively and to run in a loss. Therefore, early detection of the potato crop disease can play a vital role in minimizing the loss of the farmers. Nowadays, artificial intelligence technologies, more specifically deep learning techniques, provide solutions to many crops disease-related problems. However, training deep learning models requires a high computational power and huge amount of data as they are data hungry models. Also, designing a custom CNN models a difficult task and there are some variations …
Enhancing Motion Detection In Video Surveillance Systems Using The Three-Frame Difference Algorithm, Suhaib Qassem Yahya Al-Hashemi, Majid Salal Naghmash, Ahmad Ghandour
Enhancing Motion Detection In Video Surveillance Systems Using The Three-Frame Difference Algorithm, Suhaib Qassem Yahya Al-Hashemi, Majid Salal Naghmash, Ahmad Ghandour
Mesopotamian Journal of Computer Science
This paper outlines a methodology for motion detection in video surveillance systems, leveraging advanced algorithms and TCP/IP networks for real-time data acquisition and analysis. The primary focus is on the implementation of the Three-Frame Difference Algorithm, which detects moving targets by analyzing the differences between three consecutive video frames. This method significantly reduces redundant data transmission and storage, addressing the challenges posed by limited wireless network capabilities. The surveillance model, designed in MATLAB using SIMULINK, integrates computer vision systems with embedded coders to facilitate effective communication and processing of video data. The results demonstrate the system's capability to detect motion …
Computer Networking And Cloud-Based Learning/Teaching Environment Using Virtual Labs Tools: A Review And Future Aspirations, Mishall Al-Zubaidie, Raad A. Muhajjar, Lauy Abdulwahid Shihabe
Computer Networking And Cloud-Based Learning/Teaching Environment Using Virtual Labs Tools: A Review And Future Aspirations, Mishall Al-Zubaidie, Raad A. Muhajjar, Lauy Abdulwahid Shihabe
Mesopotamian Journal of Computer Science
Physical laboratories for practical classrooms in computer networks can be prohibitively expensive, as well as requiring regular hardware/software upgrades. With Netkit and similar software, network laboratories can be set up in a computer lab, but the setup is complicated and each student still needs their own computer. Thanks to the Cloud-based infrastructure, Netkit is now available in pre-configured Amazon elastic compute Cloud (EC2) instances. This research reviews and introduces educational computer networks. Furthermore, a web interface is used to allow remote access to numerous lab scripts instantiated on the Cloud. This study also describes how to use the Cloud to …