New machine learning model cuts fluid simulation time from 45 minutes to 3 AI has created a sea change in society; now, it is setting its sights on the sea itself. Researchers at Osaka Metropolitan University have developed a machine learning-powered fluid simulation model that significantly reduces computation time without compromising accuracy. Their fast and precise technique opens up potential applications in offshore power generation, ship design and real-time ocean monitoring. Accurately predicting fluid behavior is crucial for industries relying…
A machine-learning algorithm to study the behavior of proteins within cells and to predict their ability to trigger neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS), Parkinson’s, and Alzheimer’s. The study published in Genome Biology A research group led by Gian Gaetano Tartaglia, Principal Investigator at the Italian Institute of Technology (IIT), developed a machine-learning algorithm to study the behavior of proteins within cells and to predict their ability to trigger neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS), Parkinson’s,…
An AI model trained on large amounts of genetic data can predict whether bacteria will become antibiotic-resistant. The new study shows that antibiotic resistance is more easily transmitted between genetically similar bacteria and mainly occurs in wastewater treatment plants and inside the human body. “By understanding how resistance in bacteria arises, we can better combat its spread. This is crucial to protect public health and the healthcare system’s ability to treat infections,” says Erik Kristiansson, Professor at the Department of…
Norah Saarman receives American Mosquito Control Association Research Fund grant to develop improved species identification method Morphology is the study of the form and structure of organisms, including their physical characteristics such as shape, size and arrangement of parts. Morphology is key to taxonomy, the science of classifying organisms, as scientists use morphology to identify and study species, as well as to explore evolutionary processes. Identifying species is challenging — even with large animals and plants, says Utah State University…
AI-enhanced IV nutrition for preemies Artificial intelligence can improve intravenous nutrition for premature babies, a Stanford Medicine study has shown. The study, which will publish March 25 in Nature Medicine, is among the first to demonstrate how an AI algorithm can enable doctors to make better clinical decisions for sick newborns. The algorithm uses information in preemies’ electronic medical records to predict which nutrients they need and in what quantities. The AI tool was trained on data from almost 80,000…
Research led by University of Toronto Professor Yu Zou aims to produce higher quality and more reliable metal parts for aerospace, automotive, energy and health-care applications Researchers at University of Toronto Engineering, led by Professor Yu Zou, are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. In a new paper, published in the journal of Additive Manufacturing, the team introduces a new framework they’ve dubbed the Accurate Inverse process optimization framework in laser Directed Energy Deposition…
Technion researchers develop a technology for encoding, retrieving, and rapidly reading data stored in DNA Researchers from the Henry and Marilyn Taub Faculty of Computer Science have developed an AI-based method that accelerates DNA-based data retrieval by three orders of magnitude while significantly improving accuracy. The research team included Ph.D. student Omer Sabary, Dr. Daniella Bar-Lev, Dr. Itai Orr, Prof. Eitan Yaakobi, and Prof. Tuvi Etzion. DNA data storage is an emerging field that leverages DNA as a platform for…
American Gastroenterological Association guideline concludes that it is not clear whether computer-aided detection systems (CADe) for colonoscopy should be recommended for routine widespread use The American Gastroenterological Association (AGA) released a new clinical guideline making no recommendation — for or against — the use of computer-aided detection systems (CADe) in colonoscopy. A rigorous review of evidence showed that artificial intelligence-assisted technology helps identify colorectal polyps. However, its impact on preventing colorectal cancer — the third most common cancer worldwide —…
An AI-powered robot that can prepare cups of coffee in a busy kitchen could usher in the next generation of intelligent machines, a study suggests. Using a combination of cutting-edge AI, sensitive sensors and fine-tuned motor skills, the robot can interact with its surroundings in more human-like ways than ever before, researchers say. The new technology, developed by a team at the University of Edinburgh, could transform robots’ ability to carry out tasks that previously could only be done by…
We all know someone who seems to defy aging—people who look younger than their peers despite being the same age. What’s their secret? Scientists at Osaka University (Japan) may have found a way to quantify this difference. By incorporating hormone (steroid) metabolism pathways into an AI-driven model, they have developed a new system to estimate a person’s biological age a measure of how well their body has aged, rather than just counting the years since birth. Using just five drops…
As the planet warms, Antarctica’s ice sheet is melting and contributing to sea-level rise around the globe. Antarctica holds enough frozen water to raise global sea levels by 190 feet, so precisely predicting how it will move and melt now and in the future is vital for protecting coastal areas. But most climate models struggle to accurately simulate the movement of Antarctic ice due to sparse data and the complexity of interactions between the ocean, atmosphere, and frozen surface. In…
CAM is proposed to highlight the class-related activation regions for an image classification network, where feature positions related to the specific object class are activated and have higher scores while other regions are suppressed and have lower scores. For specific visual tasks, CAM can be used to infer the object bounding boxes in weakly-supervised object location(WSOL) and generate pseudo-masks of training images in weakly-supervised semantic segmentation (WSSS). Therefore, obtaining the high-quality CAM is very important to improve the recognition performance…
A recent paper published in the journal Engineering delves into the future of artificial intelligence (AI) beyond large language models (LLMs). LLMs have made remarkable progress in multimodal tasks, yet they face limitations such as outdated information, hallucinations, inefficiency, and a lack of interpretability. To address these issues, researchers explore three key directions: knowledge empowerment, model collaboration, and model co-evolution. Knowledge empowerment aims to integrate external knowledge into LLMs. This can be achieved through various methods, including integrating knowledge into training objectives,…
Hyperspectral imaging and AI can identify individuals using blood vessels in palms Hyperspectral imaging is a technology that detects slight differences in color to pinpoint the characteristics and conditions of an object. While a normal camera creates images using red, green, and blue, a hyperspectral camera can obtain over 100 images in the visible to near-infrared light range in a single shot. As a result, hyperspectral imaging can obtain information that the human eye cannot see. Specially Appointed Associate Professor…
Q&A with Brendan Cottrell, who investigated the use of smartphones to create 3D scans of stranded marine life that can help scientists protect marine species What inspired you to become a researcher? My interest in research began with an early love for nature, particularly the ocean and its wildlife. Drawn to conservation, I am fascinated by how technology can help study and protect marine mammals. Can you tell us about the research you’re currently working on? This research focuses on…
A new study published in Engineering presents a novel framework that combines machine learning (ML) and blockchain technology (BT) to enhance computational security in engineering. The framework, named Machine Learning on Blockchain (MLOB), aims to address the limitations of existing ML-BT integration solutions that primarily focus on data security while overlooking computational security. ML has been widely used in engineering to solve complex problems, offering high accuracy and efficiency. However, it faces security threats such as data tampering and logic corruption….
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