Machine learning
Paulina DeVito, a Ph.D. candidate in the College of Engineering and Computer Science at Florida Atlantic University, has been awarded the prestigious National Science Foundation (NSF) Graduate Research Fellowship. This honor, widely regarded as one of the most esteemed for graduate students in STEM fields, will support DeVito'
Machine learning
Scientists are working on developing tiny sensors that can detect bacterial infections and antimicrobial-resistant bacteria in bodily fluids, using a technology similar to breathalyzers. This could provide affordable and rapid diagnostic tests, leading to improved treatment plans and helping to combat antibiotic resistance. The sensors would be designed to detect
Machine learning
As the world grapples with the impact of artificial intelligence (AI) across industries, the demand for skilled professionals in AI and data science has skyrocketed. The United States, home to some of the world's most prestigious institutions for data science and AI, stands at the forefront of this
Machine learning
Researchers at the Chengdu University of Technology have successfully developed an artificial neural network that can accurately predict drilling performance in the petroleum industry. The team, led by Xiong Xiuli, used a back-propagation artificial neural network (BP-ANN) to train a drilling performance prediction function based on field data from a
Machine learning
Research from Islamic University of Najaf, Iraq, has introduced a new machine learning algorithm to predict pest and disease management in sustainable food and agriculture. The algorithm, called Pest and Disease Management Machine Learning Algorithm (PDM MLA), utilizes data-driven predictive modeling to analyze weather, soil parameters, and crop health data
Machine learning
A novel approach to quantification of active pharmaceutical ingredients in ophthalmic preparations has been developed, addressing a significant challenge in sustainability research. The study, led by researchers from King Abdulaziz University, employs machine learning-enhanced UV-spectrophotometric chemometric models to concurrently quantify latanoprost, netarsudil, benzalkonium chloride, and two related compounds. This breakthrough
Machine learning
Data from a recent study have shed new light on the capabilities of artificial intelligence (AI) in predicting preconception outcomes. Researchers from Army Medical University have used five machine-learning algorithms to analyze data from a cohort of 4,097 couples, recruited from the Chongqing Health Center for Women and Children,
Machine learning
Researchers from Technical University Dresden (TU Dresden) have developed a machine learning-based approach for accurate intraoperative liver tumor classification, potentially improving surgical outcomes and reducing recurrence risks. According to the study, the method uses fiber-based attenuated total reflection infrared (ATR IR) spectroscopy to analyze fresh liver tissue from surgical patients,
Machine learning
Researchers have developed OocystMeter, a software that uses machine learning to automate the segmentation of malaria oocysts from images of mosquito midguts. The tool helps overcome challenges in determining oocyst size and numbers by leveraging a high-quality dataset of 11,178 Plasmodium falciparum oocysts in Anopheles gambiae midguts annotated by
Machine learning
Researchers at Islamic University have developed an IoT-based crop yield prediction system that integrates advanced sensing technologies, communication protocols, machine learning algorithms, and real-time monitoring to optimize crop production. The system measures essential soil nutrients and climatic conditions, allowing for data-driven decision-making and efficient resource management. By analyzing the data,
Machine learning
Researchers from the Islamic University have made significant progress in developing an autonomous system for grapevine pruning and harvesting using advanced technologies like LiDAR, SLAM, RGB-D cameras, Convolutional Neural Networks (CNNs), proximity sensors, and Wireless Sensor Networks (WSNs). This innovative system has shown impressive results in improving accuracy and speed,
Machine learning
A new report from a research team at the University of Aveiro in Portugal details the development of a novel dataset and approach to gait-based user identification using optical Fiber Bragg Grating (FBG) sensor-based accelerometers. The research aims to address the gap in previous works in this area, which were
